tag:blogger.com,1999:blog-74250524518054577712024-03-05T08:26:34.032-08:00Driver safety and driving simulators
Driver safety is related to driver training, driver impairment, individual characteristics of the driver and cultural differences. So, it's a multifaceted theme that covers different aspects. In this blog I want to present short articles on these aspects and the significance of car driving simulators, and I hope you enjoy reading them. DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.comBlogger11125tag:blogger.com,1999:blog-7425052451805457771.post-8453732082108522852017-10-17T00:01:00.005-07:002017-10-17T00:01:56.378-07:00Cockpit vs desktop driving simulatorsWhen people think of a <a href="http://cs-driving-simulator.com/" target="_blank">driving simulator</a>, they usually see a frame with a car seat and three monitors attached on top of the frame. In most cases, driving simulators are used for driver training. The development started in the 1990's and became more popular during the last five years. They usually run on a windows computer with a advanced graphics board with 3 to 4 out put channels. In most cases, there are three graphics channels where each channel is presented on a separate monitor. There's a channel for the forward out of the window view, one for the left view and one for the right view. The horizontal viewing angle covers 180 to 210 degrees horizontal field of view (FOV). Inside each channel a rearview mirror is inserted, so basically there's an almost 360 degrees horizontal FOV.<br />
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For training, the most important part consists of the software. The more part-tasks of driving are teached and trained, the better the simulator. Its important that the simulator training addresses the same skills as driving in a real car. These skills must be rehearsed a lot in order to become automated by the driver. In that case, they require less attention and the driver can attend better to the surroundings and to unexpected events, which greatly enhancs traffic safety.<br />
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The best driving simulators have a higher training value. Yet, strangely, this is not what driving instructors generally look for. They often see a driving simulator as a marketing trick, to show the world how advanced they are. For that, its important for them how the simulator looks.<br />
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The price of a driving simulator is a sum of three things:<br />
- the software<br />
- the required hardware: a computer with a high-end GPU (graphics board), 3 or 4 monitors, and set of actuators (steering wheel, pedals, gear shifter and buttons and switches) anda sound system<br />
- the additional hardware, for example a cockpit with a car seat or a motion platform.<br />
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The software and the required hardware are essential. The additional hardware is NOT essential. You can do without a very expensive motion platform or an expensive cockpit.<br />
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Desktop simulators have the software and the required hardware, but they don't have the addidtional hardware. <a href="http://cs-driving-simulator.com/" target="_blank">Carnetsoft sells desktop simulators</a> or just simply the software and the price for a compete system is lower than 5000 euro. Other sellers of driving simulators such as <a href="http://www.stsoftware.nl/" rel="nofollow" target="_blank">ST Software</a> or <a href="https://www.greendino.nl/" rel="nofollow" target="_blank">Green Dino</a> sell cockpit simulators at prices between 15000 and 20000 euro. This big difference in prices is mainly for the cockpit, a compinent that is not really needed.DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-47344151243406274712016-04-06T10:30:00.000-07:002017-10-17T00:07:02.231-07:00Driver training and driving simulators<div style="text-align: justify;">
I would like to draw the reader's attention to a blog that focusses on <a href="http://cs-driving-simulator.com/driving-simulator.html" target="_blank">driving simulators and driver training</a>. Especially the following blog posts may be of interest to anyone interested in driver training and simulators:</div>
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<a href="https://drivingsimulatorsite.wordpress.com/2016/04/05/the-advantages-of-using-a-driving-simulator-for-driver-training/" target="_blank">The advantages of using a driving simulator for driver training</a> discusses the fact that the traditional form of driver training in a learner car does not convey the most optimal form of training for car driving. Driving a car requires complex multitasking where a large number of tasks are performed simultaneously. This has very specific training requirements that are better met in a <a href="http://cs-driving-simulator.com/" target="_blank">driver training simulator</a>.</div>
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<a href="https://drivingsimulatorsite.wordpress.com/2016/04/05/task-automation-in-car-driver-education/" target="_blank">Task automation in car driver education</a> zooms in on the task automation aspect that is trained specifically in a driving simulator. When a driver is overloaded because the driving environment demands more attention than the driver can allocate, a phenomenon called 'cognitive tunneling' occurs that increases accident risk.</div>
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<a href="https://firefly001.edublogs.org/" target="_blank">Practice is all in driver training</a> argues that a good driver has practiced a lot in all relevant traffic tasks and that simulators are very proficient in giving a lot of consistent practice to the learner driver. Specific driving tasks are practiced without the distractions and stress that comes with driver training in a learner car on public roads. Also, a <a href="https://drivingsimulatorsblog.wordpress.com/">driver training in a driving simulator</a> ensures that the trainee gets sufficient practice in all driving related tasks. Also check this post about the <a href="https://driversafetyblog.blogspot.nl/2017/10/cockpit-vs-desktop-driving-simulators.html" target="_blank">type of car driving simulator</a>.</div>
DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-29796227309012670252016-04-03T09:57:00.000-07:002017-10-01T04:10:53.548-07:00Differences in quality levels of driving schools<div align="left" style="background-color: white; font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 12px; line-height: 18px;">
Some driving schools perform consistently well while other perform not so well. There has been some research into determining factors that contribute to the quality of driver training, and the amount of practice in relevant driving tasks appears to be a very important factor. Lack of driving experience is probably the most important reason why young drivers fail for their driving exams or are overrepresented in the accident statistics. This suggests that driving schools with an excellent track record give their students a lot of driving experience in various driving tasks. This suggests that it is not a very good idea to apply for crash courses that promise a curriculum that has been reduced in time to just a couple of weeks. It also suggests that a learner permit where young drivers are supervised by an experienced driver and have to practice a lot while they are only allowed to drive in favourable circumstances (for example only during daylight) is probably a good idea. It has never been proved that supervision by professional instructors results in better drivers or higher pass rates at exams, compared to supervision by parents. All in all, extensive practice appears to be the most important factor in passing of failing for the driving test.</div>
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Quality of the driving school is an important factor in the choice of a driving school by a learner driver. In most countries it is difficult for a learner driver to find information about the quality of driving schools. In the Netherlands, around 7750 driving schools were registered in 2012. All driving instructors have to be licenced and all have followed extensive training to become a registered instructor. In order to apply for a driving test, 40 lessons (one hour per lesson) are required, on average, in a learner car on public roads. The instructor determines when the learner driver is ready to pass for the test. Still, year after year the average pass ratio for the driver test (first time) is around 50%.</div>
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In the Netherlands the pass ratios of driving schools are publicly available via the website of the examination institute (CBR). This information is generally available to the public and is used by learner drivers to choose a driving school for their driver training. A number of driving schools have consistent high scores while other driving school consistently perform poorly on pass ratio. Lets define a good driving school as a driving school where more than 75% of all students pass the first time they do the driving test. Over a large sample of driving schools, around 12,5% of all driving schools can be qualified as 'good', according to this definition. If we define a poor driving school as one where only 25% of all students pass for their exam the first time, then around 17,5% of all driving schools can be considered 'poor'. 70% of all driving schools are then 'average'.</div>
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The 'good' driving schools generally attract a lot more learner drivers. They do well economically, while the 'poor' driving schools often struggle to survive, because the market is highly competitive. A pass percentage lower than 25% is low according to Dutch standards, whereas a pass ratio of 50% is considered 'normal'. These driving schools can benefit strongly by <a href="http://cs-driving-simulator.com/" style="color: #0033ff; text-decoration: none;" target="_blank">using a car driving simulator</a> to increase the level of practice and task automation in their students. This will improve the quality of driver training for these low performing driving schools, because <a href="http://cs-driving-simulator.com/" target="_blank">the simulator curriculum</a> promotes task automation and extensive practive in relevant driving tasks. It is expected that this will increase the pass ratio and thus attract more customers.</div>
DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-625691700188596172014-08-24T04:52:00.000-07:002017-10-17T00:06:22.571-07:00Driving simulators of Carnetsoft<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjTIoPd3RKpRE0YySJ60Z3dOGC2cJW0dY0TP88qH0x85AKPTZiPNjFjK5EVz5ptNqWX2Id85eteUX7nzZ4oFotdenh1fausVsK5GAaFjPUQ4a2cr-LL4KDmh6R7GvAxkPrQ4s75CaAd-E8/s1600/Carnetsoft-website.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjTIoPd3RKpRE0YySJ60Z3dOGC2cJW0dY0TP88qH0x85AKPTZiPNjFjK5EVz5ptNqWX2Id85eteUX7nzZ4oFotdenh1fausVsK5GAaFjPUQ4a2cr-LL4KDmh6R7GvAxkPrQ4s75CaAd-E8/s1600/Carnetsoft-website.jpg" width="320" /></a></div>
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Carnetsoft <span style="background-color: white; font-family: "verdana" , "arial" , "helvetica" , sans-serif; font-size: 12px; line-height: 18px; text-align: justify;">provides<a href="http://cs-driving-simulator.com/" target="_blank"> low-cost professional car driving simulators</a> for driver education and driving schools. Compared with other manufacturers, <a href="http://cs-driving-simulator.com/driving-simulator.html" target="_blank">the driving simulators of Carnetsoft</a> are by far the most cost-effective. A complete desktop systems with 210 degrees field of view costs only 4.999,- euro. This includes all driver training software, software for training of safety awareness, a high-end computer, 4 x 23 inch monitors (HD), a control unit, webcam to track the head movements and a sound system. This car simulator has a number of advantages compared to traditional driver training in a learner car.</span><br />
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<span style="font-family: "verdana" , "arial" , "helvetica" , sans-serif;"><span style="background-color: white; font-size: 12px; line-height: 18px;">There's also another blog about <a href="https://drivingsimulatorsblog.wordpress.com/" target="_blank">driver safety and car driving simulators</a> you may be interested in.</span></span><br />
<span style="font-family: "verdana" , "arial" , "helvetica" , sans-serif;"><span style="background-color: white; font-size: 12px; line-height: 18px;">This is<a href="https://cardrivingsimulators.wordpress.com/" target="_blank"> the most advanced low-cost driving simulator</a> you will find on the market.</span></span><br />
<span style="font-family: "verdana" , "arial" , "helvetica" , sans-serif;"><span style="background-color: white; font-size: 12px; line-height: 18px;"><a href="https://driversafetyblog.blogspot.nl/2017/10/cockpit-vs-desktop-driving-simulators.html" target="_blank">Driving simulators</a> come in various forms, some a desktop systems and others as cockpit simulators.</span></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">The following article is an unpublished
experiment from <a href="http://cs-driving-simulator.com/downloads/thesis-van-winsum.pdf" target="_blank">my thesis, from adaptive control to adaptive driver behaviour</a>. It
was performed in a <a href="https://www.rijschool-simulator.nl/" target="_blank">research car driving simulator</a>. For references the reader is referred to this thesis. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">In a <a href="http://www.bizycart.com/instrumentation-the-driving-simulator/" target="_blank">driving simulator experiment</a> the relation between preferred time-headway in
steady-state car-following and operational competence in braking reactions was
studied. The hypothesis that drivers with smaller preferred time-headways are
able to react faster or generate a faster motor response per se was not
confirmed. Also, no evidence was found for differences in perceptual processes
related to the detection of braking by the lead vehicle between short
followers and drivers with a larger preferred time-headway. The results suggest
that short followers generate a faster motor response when there is some
uncertainty concerning the level and duration of deceleration of the lead
vehicle in case it brakes. The results suggest that short followers differ from
long followers in the ability to transform visual feedback to a required motor
response. However, the presence of brake lights is required for the relation
between operational performance and choice of time-headway to hold, possibly
because a change in feedback requirements, i.e. the absence of brake lights, is
more detrimental for skilled performers.<o:p></o:p></span></div>
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<b><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Introduction</span></b><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"><o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Choice of time-headway (THW) in car-following has been associated with
task-related factors and with factors related to temporary state in a number of
studies. The results of these studies may be explained in terms of an adaptation
of choice of THW to perceived performance decrements in operational skills
related to braking. The importance of task-related factors appears from the
studies of Fuller (1981) and Brookhuis et al. (1991). Fuller (1981) studied
THW of truck drivers. During the late shift, consisting mainly of driving in
the dark, time-headway was significantly larger than during day time driving.
Fuller explained this as an effect of visual conditions. Brookhuis et al.
(1991) reported an increase in THW when using a car telephone while driving. The effects on THW may be explained as a
result of awareness of the effects of
task demands on the ability to detect a deceleration of a lead vehicle
resulting in an adaptation of THW to compensate for this. A number of other
studies have shown that choice of time-headway is sensitive to temporary
states. Fuller (1984) reported a time-on-task effect on THW for older truck
drivers in the late shift. After seven hours of driving, THW increased quite
strongly, accompanied by verbal reports of performance decrements, drowsiness
and exhaustion. In an experiment reported by Smiley et al. (1981) in an interactive
driving simulator, marijuana resulted in increased headway during car-following.
Smiley et al. (1986) again found that marijuana significantly increased
headway in a car-following task. Smiley et al. (1985) reported that marijuana
increased headway while alcohol decreased headway. These results strongly suggest
effects of temporary states such as fatigue or states induced by marijuana and
alcohol on preferred THW; fatigue and marijuana increase preferred THW, which
may be a reflection of an adaptation of THW to perceived adverse effects on
the braking response, whereas alcohol decreases preferred THW, possibly
because drivers overestimate their braking competence under alcohol. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The effects of task-related
factors and transient states refer to intra-individual differences. The results
suggest a process of adaptation of THW to changes in operational competence
which is influenced by task-related and state-related factors. From the same
perspective, inter-individual differences in following behaviour, may be
related to inter-individual differences in operational level competence, such
that preferred THW is adapted to limitations in braking-related competence.
These limitations in braking competence may be determined by specific skills
required for optimal braking performance. In that case drivers may adapt
time-headway to their braking skills such that the time available to reach the
same level of deceleration as the lead vehicle in case it brakes matches the
time needed by the driver to reach this level of deceleration. The former is
equivalent to the momentary time-headway. The latter may be related to braking
related skills of the driver. Extrapolated to the more general case, behaviour
on the tactical level is assumed to be adapted to operational skills. The same
reasoning was applied to speed choice in curves by Van Winsum and Godthelp
(1996). They found a strong relation between choice of speed in curves and
steering performance on straight roads, such that drivers adapt the speed in
curves to their steering competence. An important research question then
focuses on finding the relevant skills that discriminate drivers with different
preferred time-headways.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> In the normal case of braking
for a decelerating lead vehicle, the driver adjusts the timing and intensity of
the braking response to the criticality at the moment of detection of a
deceleration of the lead vehicle and the development of criticality in time.
In this, TTC information is assumed to plays an important role (e.g. Van der
Horst, 1990; Cavallo et al., 1986; Cavallo and Laurent, 1988; Lee, 1976),
although it is not clear how TTC information affects the braking response.
However, when the driver is instructed to brake as fast as possible as soon as
a deceleration of the lead vehicle is detected, the timing and intensity of
braking are expected to depend on the limits of perceptual and motor skills
instead of TTC information. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The dominant view in studies of
braking has been that perceptual limitations, instead of response mechanisms,
are responsible for rear-end collisions. In the literature braking skill is
generally studied as the ability to brake as fast as possible instead of the
ability to tune the timing and intensity of braking to the dynamic
requirements of the situation. This is somewhat surprising given the
ecological desirability to brake with a velocity and intensity that matches
the requirements of the situation. In the literature, brake reaction time
(BRT), or alternatively, perception-response time is used as an index for
braking performance. This is defined as the interval between the onset of the
stimulus, usually the brake lights of the lead vehicle, and the moment the foot
touches the brake. BRT differs from reaction time (RT) as it is normally
applied in experimental psychology. RT for a decelerating lead vehicle is
measured as the interval between the moment the lead vehicle starts to decelerate
and the moment the foot is retracted from the accelerator pedal. Although BRT
includes reaction time, it covers the time to move the foot from the
accelerator to the brake pedal as well. A reduction of BRT has been proposed as
a means to reduce the number of rear-end collisions. Experiments that were
aimed at finding factors that decrease BRT have been carried out for years
(see for example McKnight and Shinar, 1992). For this purpose, center
high-mounted stop lamps (CHMSL) have become standard equipment in passenger
cars in the United States, although the evidence for actual reductions in BRT
by these lamps is limited (McKnight and Shinar, 1992, Sivak et al., 1981).
There is however some evidence that CHMSL reduces the number of rear-end
accidents (see for instance Rausch et al., 1982). Thus, the scientific answer
to the assumed perceptual limitations in braking has been to decrease the
detection time by technical means. Other factors have been found that affect
BRT as well. Johansson and Rumar (1971) found that BRT to anticipated events
is faster than for unexpected events. Olson and Sivak (1986) reported an
average BRT to expected stimuli of about 0.7 s. while it was about 1.1 s. to
unexpected stimuli. The expectancy effect was also reported by Sivak (1987).
The nature of the stimulus affects BRT as well. In car-following situations BRT
is faster compared to other situations such as the detection of a stationary
police car (Sivak, 1987). Furthermore, distance headway has a substantial
effect on BRT (see for instance Brookhuis and De Waard, 1994, McKnight and
Shinar, 1992 and Sivak et al., 1981). <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> From an adaptation perspective,
perceptual skills related to the detection of a deceleration of the lead
vehicle may be a determining factor for choice of time-headway. In that case a
relation is expected between preferred THW and reaction time. The reaction
time interval consists of a series of information-processing stages. The
additive factor method, introduced by Sternberg (1969), assumes that these
processing stages are serial and that the duration of these stages are
independent. It is a method for studying the locus of effect of differences in
RT. Several task variables are known to affect RT via effects on specific
information-processing stages. According to the additive factor method, if two
task variables interact in their effect on RT a common processing stage is
involved. Additive effects of two task variables on RT are indicative of
separate effects on different processing stages. In this chapter, the additive
factors method is used to determine whether differences in RT as a function of
preferred THW are caused by differences in the input side or the output side of
the information-processing chain. Figure 1 shows the successive
information-processing stages that are assumed to determine RT.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> Stimulus degradation is known
to affect the stimulus encoding stage on the input or perception side of
information-processing (Sanders, 1990, Frowein, 1981). In braking for a decelerating
lead vehicle, the absence of brake lights (BL) may be regarded as a severe
form of stimulus degradation. Alternatively, differences in RT may have a
locus of effect on the output or response preparation side of the
information-processing chain. Time uncertainty, manipulated by means of
presentation of a warning signal (WS) in advance of stimulus presentation is
known to affect the output or motor side of the information-processing chain.
Sanders (1980a) and Frowein (1981) reported additive effects of time uncertainty
and stimulus degradation. This indicates that different
information-processing stages are affected by signal quality and time
uncertainty. Sanders (1980b) reported an interaction between time uncertainty
and instructed muscle tension on RT. This suggest that the factor WS
affects the motor-adjustment stage.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Figure 1. Information-processing stages during the reaction time
interval <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">as discussed by Frowein (1981)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Also, Spijkers (1989) reported an interaction between time uncertainty
and response specificity suggesting an effect of time uncertainty, or WS, on
motor adjustment. Motor adjustment represents the stage where the state of
motor readiness is modulated by straining the muscles. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The additive factor method has
not only been applied to the study of information-processing stages, it has
also been used to study individual differences related to, for example,
dementia (Jolles, 1985) and hyperactivity in children (Spijkers and Curfs,
1986). This is important since the present study uses the additive factor
method to explore information-processing factors underlying individual
differences in behaviour.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> In summary, if short followers
differ in RT from drivers who follow with a larger THW, the reasons for
differences in RT may be located on the input and/or output side of the
information-processing chain. It can then be tested whether short followers
differ from drivers with a larger preferred THW in the stimulus encoding stage
with the BL manipulation. If drivers with a larger preferred THW are less
efficient or slower in stimulus encoding, stimulus degradation is predicted to
result in a relatively larger effect on RT for these drivers. Thus, differences
in stimulus encoding as a function of preferred THW expresses itself as an
interaction between preferred THW and the BL manipulation on RT. This would
mean that differences in RT as a function of preferred THW are caused by faster
detection by short followers of a deceleration of the lead vehicle.
Alternatively, an interaction between preferred THW and the WS manipulation on
RT such that RT of short followers is less affected by the WS manipulation
than the RT of drivers with larger preferred THW, would suggest that short
followers reach the state of required motor readiness faster. In that case,
differences in RT are related to response mechanisms instead of perceptual
mechanisms. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> Choice of time-headway may also
be related to the speed at which the driver is able to move the foot. In that
case choice of time-headway may be an adaptation to individual differences in
motor speed. However, the additive factor method has never been successfully
applied to the motor phases of response execution. This means that there is
not sufficient reason to apply this method to the examination of motor
execution during the braking response. Also, there are no theoretical
predictions for the effects of WS and BL on the duration of the motor phases
that follow the RT interval when the subjects are required to brake as fast as
possible. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> In summary, the following
questions are examined in the present experiment :<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">1) Is preferred time-headway related to differences in reaction speed to
a deceleration of the lead vehicle, and if so, are the differences located on
the perceptual or the response side of the information-processing chain.<o:p></o:p></span></div>
<div class="MsoNormal" style="line-height: 120%; margin-bottom: .0001pt; margin-bottom: 0cm; margin-left: 42.5pt; margin-right: 1.0cm; margin-top: 0cm; mso-hyphenate: none; mso-list: l0 level1 lfo1; tab-stops: -72.0pt -36.0pt 0cm 14.75pt 29.5pt 49.2pt 63.95pt 78.7pt 93.45pt 108.0pt 123.0pt 137.75pt 152.5pt 167.25pt 180.0pt 196.8pt 211.55pt 226.3pt 241.05pt 255.8pt 270.6pt 285.35pt 324.0pt; text-align: justify; text-indent: -14.15pt;">
<!--[if !supportLists]--><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">2) <span style="font-family: "times new roman"; font-size: 7pt; line-height: normal;"> </span></span><!--[endif]--><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Is preferred time-headway related to skills involved in motor execution.
<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The experiment was performed in
an interactive simulator. This allows full control over the behaviour of the
lead vehicle and accurate on-line measurement of time-related variables. <o:p></o:p></span></div>
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<b><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Method</span></b><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<i><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Apparatus</span></i><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">. The experiment was performed in the driving simulator of the Traffic
Research Centre (TRC). This fixed-based simulator consists of two integrated
subsystems. The first subsystem is a conventional simulator composed of a car
(a BMW 518) with a steering wheel, clutch, gear, accelerator, brake and
indicators connected to a Silicon Graphics Skywriter 340VGXT computer. A car
model converts driver control actions into a displacement in space. On a
projection screen, placed in front, to the left and to the right of the
subject, an image of the outside world from the perspective of the driver with
a horizontal angle of 150 degrees is projected by three graphical videoprojectors,
controlled by the graphics software of the simulator. Images are presented with
a rate of 15 to 20 frames per second, resulting in a suggestion of smooth movement.
The visual objects are buildings, roads, traffic signs, traffic lights and
other vehicles. The sound of the engine, wind and tires is presented by means
of a digital soundsampler receiving input from the simulator computer. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The second subsystem consists
of a dynamic traffic simulation with interacting artificially intelligent
cars. For experimental purposes different traffic situations can be
simulated. The simulator is described in more detail elsewhere (Van Wolffelaar
& Van Winsum, 1992 and Van Winsum & Van Wolffelaar, 1993). <o:p></o:p></span></div>
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<i><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Procedure</span></i><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">. The experiment was preceded by another one in which the same subjects
had been driving in the simulator for about one hour. Instructions were
delivered in writing. Preferred time-headway was measured as follows.
Subjects were instructed to drive 80 km/h where possible and to follow the
lead vehicle at the distance they would choose in real traffic. A lead vehicle
in front of the simulator car controlled its speed such that a THW of 1 second
was maintained. After a while the lead vehicle started to maintain a constant
speed of 80 km/h and the subject was required to choose the preferred THW. As
soon as the preferred THW was reached the subject pressed a button. Time-headway,
calculated as distance headway divided by the speed of the simulator car in
m/s, at the moment the button was pressed was used as a measure for preferred
time-headway (THW<sub>pref</sub>). <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> After this, braking performance
was measured. Four trials were executed successively. A trial consisted of
braking with the instruction to brake as fast as possible followed by braking
with the instruction to brake normally. Only the results of braking responses
with the instruction to brake as fast as possible are reported here. Subjects
were requested to drive with a constant speed of 80 km/h and not to exceed the
lane boundaries. Speed (in km/h) was continuously projected on the screen in
front, allowing subjects to monitor the behaviour of the lead vehicle. The lead
vehicle maintained a constant time-headway of 1 second. After a while, i.e.
about 1 minute, it braked to a full stop
with a deceleration of 6 m/s². In two trials, a warning signal (WS) was
presented 1 second before the lead vehicle braked, while in the other two
trials no WS was presented. A WS consisted of three stars projected on the
screen during 1 second. Subjects were told a WS indicated that the lead
vehicle might brake after 1 s. They were requested not to release the right
foot from the accelerator until they were sure that the lead vehicle actually
braked. The lead vehicle only braked when the accelerator position was not
more than 5% less than 1 second before. This means that braking of the lead
vehicle never occurred while the S was releasing the foot from the accelerator
pedal. In two trials the lead vehicle carried brake lights during braking,
while in the other two trials the brake lights were switched off. This constitutes
the BL manipulation. The trials were administered in four different orders
(see table 1). Subjects were randomly assigned to one of these orders with the
restriction that the same number of subjects were represented in each order
of trials. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Table 1. Order of trials. ! means not<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> Order<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <u> 1 2 3 4 <o:p></o:p></u></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">A
WS- BL WS-!BL !WS- BL !WS-!BL <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">B
WS-!BL
WS- BL !WS-!BL !WS- BL<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">C !WS-
BL !WS-!BL WS- BL WS-!BL<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">D !WS-!BL !WS- BL
WS-!BL WS- BL <o:p></o:p></span></div>
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<i><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Data collection and analysis</span></i><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">. Speed, distance-headway, time-headway, accelerator- and brake
position were sampled with a frequency of 10 Hz. Reactions to braking of the
lead vehicle were stored in an event file. These events were monitored with a
frequency of 50 Hz. The following events were stored:<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 1) time of presentation of WS<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 2) time of braking of lead vehicle (t<sub>0</sub>)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 3) time at which accelerator position was decreased >= 5% since 2
(t<sub>acc</sub>)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 4) time at which brake pedal position was >= 5% (t<sub>br</sub>)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 5) time at which a brake maximum was reached (t<sub>maxbr</sub>)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">- 6) value of brake maximum (MAXBR)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Reaction time (RT) was calculated as 3-2. Movement time (MT) was
calculated as 5-3. MT was recoded as a missing value when there was more than
one brake peak in a trial. The occurrence of more than one brake peak
indicates that the subject braked, retreated the foot, and pushed the brake again.
This indicates that the instruction to brake as fast as possible was not
followed and it occurred in two subjects. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The effects of WS and BL on RT
and MT were tested with an analysis of variance repeated measurement design.
Preferred time-headway was treated as a between-subjects factor. <o:p></o:p></span></div>
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<i><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Subjects</span></i><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">.</span><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 78 subjects participated in the experiment, 38 were male and 40 were
female. 40 subjects were younger than 25 years of age, and 38 were older, but
not older than 40. The average number of years the subjects were licensed to
drive a car was 7.38 (sd. 4.87), total kilometrage was 88600 km (sd. 134355) on
average, while the average annual kilometrage was 11786 (sd. 14794).<o:p></o:p></span></div>
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<b><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Results</span></b><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"><o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Three groups (THW<sub>pref</sub> groups) of equal size were created from
the distribution of preferred time-headway. The group 'short' followers
includes the subjects with smallest preferred time-headway, the group 'medium'
followers contains subjects in the middle range of preferred time-headway,
while the group with highest preferred time-headway are the 'long' followers.
The average time-headways of these groups can be seen in table 2. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Table 2. Average time-headway <o:p></o:p></span></div>
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<u><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">group THW n <o:p></o:p></span></u></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">short 1.58 26<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">medium 2.13 26<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">long 3.16 26<o:p></o:p></span></div>
</div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">The effects of THW<sub>pref</sub> groups on RT and MT are listed in
table 3.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Table 3. Effects of THW<sub>pref</sub> groups on RT and MT, df between
brackets.<o:p></o:p></span></div>
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<u><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">variable F p <o:p></o:p></span></u></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">RT 0.25 (75,2) 0.790 <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">MT 0.75 (72,2) 0.477<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Short followers did not exhibit a faster RT than drivers with a larger
preferred time-headway. Also the duration of the movement phase of braking (MT)
was not significantly affected by THW<sub>pref</sub> groups..<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The effects of WS and BL on RT
are shown in figure 2. There was a significant main effect of WS on RT
(F(79,1)=45.91, p<0.001). The effect of BL on RT was statistically
significant as well (F(79,1)= 290.41, p<0.001). The interaction was not
significant (F(79,1)=2.18, p=0.144). WS and BL had additive effects on RT in
the expected direction. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The effects of WS and BL on MT
are presented in figure 3. WS had a significant main effect on MT
(F(76,1)=12.50, p<0.001). The effect of BL was not significant
(F(76,1)=0.21, p<0.646). The interaction was not significant (F(76,1)=0.49,
p<0.487).<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The interactions with THW<sub>pref</sub>
group are listed in table 4. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Table 4. Interactions of THW<sub>pref</sub> group with WS and BL. <o:p></o:p></span></div>
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<u><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">variable effect F p <o:p></o:p></span></u></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">RT THW<sub>pref</sub>xWS 0.00
(75,2) 1.000<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> THW<sub>pref</sub>xBL 0.02 (75,2) 0.985<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> THW<sub>pref</sub>xWSxBL 0.35 (75,2) 0.708<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">MT THW<sub>pref</sub>xWS 1.64
(72,2) 0.200<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> THW<sub>pref</sub>xBL 4.31 (72,2) <u>0.017</u><o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> THW<sub>pref</sub>xWSxBL 0.63 (72,2) 0.537<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">The interactions of WS and BL with THW<sub>pref</sub> groups on RT were
not significant. Thus, no evidence was found for differences between short
followers and drivers with a larger preferred THW in the stimulus encoding and
motor-adjustment stages. The interaction between THW<sub>pref</sub> and BL on
MT was significant. This interaction was analyzed in more detail. MT of the
two extreme THW<sub>pref</sub> groups (short and long followers) were compared
for the BL and non-BL trials separately. MT during BL trials was significantly
faster for short followers compared to long followers (F(49,1)=4.17,
p<0.05). During non-BL trials MT was not significantly different for short
and long followers however (F(49,1)=0.72, p=0.401), see figure 4. This means
that only in trials in which the brake lights were switched on short followers
moved their foot faster to the maximum level compared to long followers.
Post-hoc analyses revealed that the THW<sub>pref</sub> x BL interaction on MT
was mainly caused by an effect of preferred THW on MT for the first braking
trials in which the lead vehicle carried brake lights. The results of
regression analyses with MT as a dependent variable and preferred THW as an
independent variable are listed in table 5, for BL and non-BL trials
separately. It can be seen that only for first trials in which the brake lights
on the lead vehicle were switched on MT was a function of preferred THW, such
that drivers with a smaller preferred THW moved their foot faster from the
accelerator pedal to the brake maximum. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Figure 2. RT as a function of WS and BL.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Figure 3. MT as a function of WS and BL. <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Table 5. Effects of regression analyses of THW<sub>pref</sub> on MT for
trial orders 1, 2, 3 and 4 <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">and for BL and non-BL trials separately (df between brackets).<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <u> Order Beta F
<o:p></o:p></u></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">BL trials<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 1 0.50 12.67 (38,1) ** <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 2 0.02 0.02 (34,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 3 0.29 3.59 (40,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 4 -0.29 3.08 (34,1) <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">non-BL trials<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 1 -0.18 1.06 (33,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 2 0.18 1.41 (40,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 3 -0.17 0.96 (34,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> 4 -0.11 0.49 (40,1)<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">** = p < 0.01; * = p < 0.05
<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">Figure 4. Average MT for short and long followers, for BL and non-BL
trials.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">It was tested whether this had caused the THW<sub>pref</sub> x BL
interaction to become significant. The THW<sub>pref</sub> x BL interaction was
examined for the last two trials (3 and 4) only. This interaction was not
significant (F(75,2)=2.18, p=0.120), while the THW<sub>pref</sub> x BL
interaction was significant for the first two trials (1 and 2) only
(F(72,2)=4.52, p<0.05). <o:p></o:p></span></div>
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<b><span lang="EN-US" style="font-family: "times roman"; font-size: 12.0pt; letter-spacing: -0.1pt; line-height: 120%;">Discussion and conclusions</span></b><span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> <o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;">The experiment was performed in an interactive driving simulator.
Drivers were subjected to a number of scenarios in which the lead vehicle
braked sharply from 80 km/h until it came to a full stop. The lead vehicle
started to brake at a time-headway of 1 second. Subjects were instructed to
brake as fast as possible as soon as the deceleration of the lead vehicle was
detected. Subjects knew in advance that the lead vehicle would brake.
Presentation of a warning signal (on/off) and application of brake lights on
the lead vehicle (on/off) were administered in a within-subjects design,
resulting in four braking conditions.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The theoretical perspective of
the present study was that drivers adapt time-headway to their braking skills
in such a way that the time available to reach the same level of deceleration
as the lead vehicle in case it brakes matches the time needed by the driver to
reach this level of deceleration. Individual differences in choice of
time-headway are then expected to be related to individual differences in
braking skills. Braking for a lead vehicle requires a number of skills varying
from perceptual skills needed for a fast detection of decelerations of the lead
vehicle to perceptual-motor skills involved in tuning the motor response to
visual input. This study was aimed at finding the relevant skills related to choice
of time-headway during car-following.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> In the literature on braking
perceptual mechanisms, such as the estimation of time-to-collision and the
detection of deceleration of a lead vehicle, are emphasized as important
skills. Also, the ability to initiate braking as fast as possible is seen as an
important factor in rear-end collisions. Starting from the existing literature,
it was investigated whether choice of time-headway is related to the ability
to initiate braking as fast as possible. Using the logic of the additive factor
method the locus of effect for differences in reaction time was examined. The
stimulus encoding stage of the information-processing chain was manipulated by
switching the brake lights of the lead vehicle on or off. This resembles a
manipulation of the factor stimulus degradation. The motor-adjustment stage was
manipulated by the presence or absence of a warning signal 1 second in advance
of stimulus presentation (deceleration of the lead vehicle). The presentation
of a warning signal affects time uncertainty, a factor that is known to affect
the motor-adjustment stage. The manipulations both had statistically
significant additive effects on reaction time. This confirms the results
reported in the experimental psychological literature that different stages are
selectively affected by these two manipulations. However, no significant
effect of preferred time-headway was found on reaction time. Also, no
significant interactions of preferred time-headway with either the brake lights
or the warning signal manipulations were found on reaction time. This indicates
that choice of time-headway is not related to reaction time. It also indicates
that choice of time-headway is not related to the speed at which a deceleration
is detected or to the speed at which the state of motor-readiness is reached.<o:p></o:p></span></div>
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<span lang="EN-US" style="font-family: "times roman"; letter-spacing: -0.1pt;"> The results on movement time
(MT) revealed a different pattern. The factor warning signal had a significant
effect on movement time; presentation of a warning signal resulted in a larger
movement time. This result is difficult to explain. Generally, in laboratory
experiments no effects of time uncertainty on movement time are found (see f.i.
Frowein, 1981). A possible explanation is that the absence of a warning signal
resulted in a longer reaction time and thus a higher criticality at the moment
the motor response was initiated. This required the subjects to speed up the
motor response. However, the absence of a significant effect of the factor
brake lights on movement time makes this explanation highly unlikely because
the brake lights manipulation had much stronger effects on reaction time.
If there are effects of criticality on
movement, the manipulation of brake lights is expected to have a greater effect
on movement time than the warning signal manipulation. This obviously was not
the case. Also, since the subjects were instructed to brake as fast as possible,
criticality effects were not expected. There was no significant effect of
preferred time-headway on movement time. This means that there is no evidence
that short followers differ from drivers with a larger preferred time-headway
in the ability to generate a faster motor response per se. However, the
interaction between preferred time-headway and the brake lights manipulation
on movement time was significant. Only when the lead vehicle carried brake
lights, short followers moved their foot faster to the brake maximum than
drivers with a larger preferred time-headway. The relation between preferred
time-headway and movement time was absent when the lead vehicle did not carry
brake lights. This is partly consistent with the results reported by Marteniuk
et al. (1988) in a study of motor learning. They found that as the performer
is more skilled in the execution of a motor task, changing the feedback
conditions strongly interferes with motor execution. The absence of brake
lights may be regarded as a strong change in feedback conditions, since the
brake lights of the lead vehicle are an important cue for the driver in
braking. Post-hoc analysis revealed that the interaction of preferred
time-headway with the brake light manipulation on movement time was mainly
caused by a trial order effect. In the first braking maneuver there was a
strong effect of preferred time-headway on movement time, only if brake lights
of the lead vehicle were switched on during braking. This effect was absent in
later braking maneuvers. The first braking maneuver differs in one important
aspect from later braking trials. During later braking trials the subjects knew
the level of deceleration of the lead vehicle and the duration of its
deceleration, while this information was not available to the driver during the
first braking trial. This suggests that preferred time-headway is related to
the skill to transfer visual feedback to a required motor response. During the
first trial visual feedback had to be interpreted during the course of braking,
while during later trials the required motor response was known even before the
response was generated. This means that for later trials a standard learned
fast response could be generated while in the first trial the transformation of
visual feedback to the motor-response may have played some role. This suggests
that the differences in response execution speed as a function of preferred
time-headway are restricted to braking situations characterized by uncertainty
concerning the braking by the lead vehicle, the required deceleration and the
duration of braking, as is the case in normal car-following situations. <o:p></o:p></span></div>
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DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com3tag:blogger.com,1999:blog-7425052451805457771.post-10475630289079627172014-06-16T03:23:00.001-07:002017-12-09T08:02:34.174-08:00Adaptation model of car driving<div class="MsoNormal" style="line-height: 120%; mso-hyphenate: none; tab-stops: 12.2pt 28.55pt 44.85pt 61.2pt; text-align: justify;">
<span lang="EN-US" style="line-height: 120%;">In my PhD thesis from 1996, I developed <a href="http://www.bizycart.com/chapter-10-thesis-traffic-psychology/" target="_blank">a model of driver behaviour</a> that was named <b>the adaptation model of car driving</b>. In this article I will present the outline of the model. In the thesis, a number of experiments were presented that were designed to test important elements of the model. All experiments were performed in a <a href="http://cs-driving-simulator.com/research-driving-simulator/" target="_blank">research car driving simulator</a> and most of the studies were published in the scientific literature.</span></div>
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<span lang="EN-US" style="line-height: 120%;"><br /></span></div>
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<span lang="EN-US" style="line-height: 120%;">The main element of the <b><a href="http://www.bizycart.com/introduction-thesis-traffic-psychology/" target="_blank">adaptation model of driver behaviour</a></b> is that it predicts that any factor that affects operational performance will </span></div>
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<ul>
<li><span style="line-height: 120%;">normally result in an adaptation of behaviour on the tactical level, </span></li>
<li><span style="line-height: 120%;">such that
constant safety margins are maintained. </span></li>
</ul>
Operational performance concerns the lateral control performance (steering) and longitudinal control performance (braking and speed control in general).<br />
<br />
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<span lang="EN-US" style="line-height: 120%;">The model represented in the following figure.</span></div>
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<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEja1W_m_Gsuto2FXDIxSIWtDPed2dzhecFvLG2cyNPdEwpePRi7UzJcac02n1V1XBlvrqbMNnUJJzM5BlGBUlFWAGo8nejHSnxrQh7o2dXnW6GDpcXaaHdkjrRXqZ9lRD3Vs5Q653iJitg/s1600/adaptation-model.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="185" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEja1W_m_Gsuto2FXDIxSIWtDPed2dzhecFvLG2cyNPdEwpePRi7UzJcac02n1V1XBlvrqbMNnUJJzM5BlGBUlFWAGo8nejHSnxrQh7o2dXnW6GDpcXaaHdkjrRXqZ9lRD3Vs5Q653iJitg/s1600/adaptation-model.jpg" width="400" /></a></div>
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<span lang="EN-US" style="line-height: 120%;"><br /></span></div>
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<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;">This model states that several
factors affect operational performance. For example, <b>temporary states</b>, induced
by alcohol or marijuana, affect psycho-motor abilities while psycho-motor
abilities affect operational performance. Also, <b>vehicle related factors</b>, <b>situational factors</b> and <b>driving experience</b> may affect operational performance
in accordance with the adaptive control models. The effects on operational
performance are perceived via a <b>feedback loop</b> by the driver, although <b>alcohol
and young age</b> may inhibit this. </span></div>
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<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;">If driving is <b>self-paced</b>, the driver adjusts
behaviour on the tactical level by either increasing speed or decreasing
headway during car-following if operational performance is improved, or by
decreasing speed or increasing headway if operational performance deteriorates. </span></div>
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<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;">If there are no opportunities to adapt behaviour on the tactical level, i.e.
when the driving task is <b>forced-paced</b>, the driver may elect in allocate more
effort to increase operational performance. </span></div>
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<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;">Adaptation of tactical behaviour or
effort allocation does not only occur as a response to momentary changes, but
also in the form of an anticipatory response. This response is the result of
learned associations between various factors and effects on operational
performance allowing an adaptation of tactical behaviour in the absence of an
effect on operational performance. For example, if the driver has learned the
effects of rain on road friction and on operational steering performance, he
may already choose a lower speed before these effects are actually experienced
during a particular period of rain.<o:p></o:p></span><br />
<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;"><br /></span>
<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;">When drivers are not able to adapt behaviour on the tactical level for whatever reason, for example, </span><br />
<br />
<ul>
<li><span style="letter-spacing: -0.1pt; line-height: 120%;">because they are intoxicated with alcohol or drugs or </span></li>
<li><span style="letter-spacing: -0.1pt; line-height: 120%;">impaired by fatigue or drowsiness, or </span></li>
<li><span style="letter-spacing: -0.1pt; line-height: 120%;">because they are inexperienced, or they overestimate their driving skills, </span></li>
</ul>
<br />
<span style="letter-spacing: -0.1pt; line-height: 120%;">the risk of traffic accidents greatly increases. So the model has a direct link with <a href="https://drivingsimulatorsblog.wordpress.com/">driver safety</a>. It also explains why vehicle factors aimed to improve safety often don't result in safety improvements in practice.</span><br />
<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;"><br /></span>
<span lang="EN-US" style="letter-spacing: -0.1pt; line-height: 120%;"><span style="letter-spacing: normal;">The complete </span><a href="http://cs-driving-simulator.com/downloads/thesis-van-winsum.pdf" style="letter-spacing: normal;" target="_blank">thesis can be downloaded here</a><span style="letter-spacing: normal;">.</span></span></div>
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DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-50208122701597536412014-06-15T06:18:00.002-07:002017-10-01T04:13:45.972-07:00De functionele visuele veldgrootte als een indicator voor de werklast tijdens het rijden<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times";">Dit is een ongepubliceerd artikel dat gepresenteerd is op een Ergonomie congres in 1999.</span></div>
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<i><span style="font-family: "cg times"; mso-ansi-language: NL;"><br /></span></i></div>
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<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Samenvatting</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Er wordt een methode
beschreven voor het meten van werklast tijdens het rijden en van kort durende
pieken in de werklast. De methode is gebaseerd op het idee dat het functionele
visuele veld inkrimpt wanneer de werklast toeneemt. De methode is getoetst in
een experiment in een <a href="http://cs-driving-simulator.com/" target="_blank">rijsimulator</a>. Hierin is de toename in werklast als gevolg
van spraak-gegenereerde boodschappen en tactiele boodschappen door een
bestuurdersondersteuningssysteem gemeten. <o:p></o:p></span></div>
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<br /></div>
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<span style="font-family: "cg times"; mso-ansi-language: NL;">INLEIDING<o:p></o:p></span></div>
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<span style="font-family: "cg times"; mso-ansi-language: NL;">In-voertuig systemen kunnen een negatief effect hebben op
de veiligheid wanneer ze de werklast verhogen of de bestuurder afleiden
(Verwey, Brookhuis & Janssen, 1996). De toegenomen werklast ten gevolge van
de interactie van de bestuurder met het in-voertuig systeem kan in sommige
omstandigheden leiden tot overbelasting. Daardoor kan de bestuurder niet alle
voor de rijtaak relevante informatie verwerken en dit kan leiden tot een
toename in het aantal fouten en late detectie van andere verkeersdeelnemers
(Rumar, 1990). Daarbij valt bijvoorbeeld te denken aan de effecten van mobiele
telefoons, navigatiesystemen en RDS-TMC. Er is inmiddels veel onderzoek
verricht naar de effecten van dergelijke in-voertuig systemen op het rijgedrag
en de veiligheid maar de resultaten zijn vaak niet eenduidig. Een toename van
de werklast zal voornamelijk plaatsvinden tijdens de interacties van de
bestuurder met het in-voertuig systeem. Het gaat dan om kortdurende pieken in
de werklast die met de gebruikelijke methoden voor het meten van werklast
moeilijk te detecteren zijn. Het zijn vooral de plotselinge pieken in de
werklast die potentieel een negatief effect hebben op de veiligheid. Immers,
wanneer de werklast voor de bestuurder voorspelbaar is zal deze proberen de
werklast te regelen door waar mogelijk het gedrag op de primaire rijtaak aan te
passen. Zo vond Harms (1991) dat een grotere werklast als gevolg van het rijden
in een complexe omgeving leidt tot een lagere snelheidskeuze. Dergelijke
gedragsaanpassingen zijn ook gerapporteerd als reactie op voorspelbare toenames
in werklast door in-voertuig systemen. Wierwille (1993a) vond dat wanneer de
complexiteit van de primair rijtaak toeneemt, bijvoorbeeld omdat de omgeving
complexer wordt, de verkeersdrukte toeneemt of wanneer er meer zijwind is, de
bestuurder minder vaak en korter naar het in-voertuig display van een
navigatiesysteem kijkt. Deze onderzoeken geven aan dat de bestuurder op en
aktieve wijze probeert de werklast te reguleren, waarbij het autorijden zelf
een hogere prioriteit heeft dan andere taken. Bij het presenteren van
informatie middels visuele displays heeft de bestuurder doorgaans de keuze om
aandacht aan de gepresenteerde informatie te geven. De automobilist zal deze
keuze in het ideale geval laten afhangen van de momentane werklast als gevolg
van de primaire rijtaak. Wanneer er een plotselinge toename is van de werklast,
bijvoorbeeld doordat een voorligger plotseling remt, zal er doorgaans voor
gekozen worden om even geen aandacht te geven aan het visuele display. Wanneer
er echter een incident optreedt tijdens het kijken naar een display kan de
bestuurder alsnog te laat reageren. Vandaar dat er ten aanzien van de visuele
werklast door in-voertuig displays voor wordt gepleit om richtlijnen op te
stellen voor de vereiste kijkduur (Average Glance Duration, AGD) en het aantal
keren dat er naar het display gekeken moet worden om de informatie op te pikken
(Mean Number of Glances, MNG). Door het meten van de AGD en de MNG kan de
visuele werklast t.g.v. een in-voertuig display vastgesteld worden. De gedacht
bij het time-sharing model van Wierwille (1993a, 1993b), waarin het meten van
de AGD en MNG een belangrijke rol speelt, is dat het visuale input kanaal
strict ‘single channel’ is en werkt volgens het alles of niets principe. Dat
betekent dat je maar naar één ding tegelijk kunt kijken, ofwel naar het
in-voertuig display, of naar buiten door de voorruit of naar iets anders. <o:p></o:p></span></div>
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<br /></div>
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<span style="font-family: "cg times"; mso-ansi-language: NL;">Tijdens het rijden is de werklast een optelling van de
door de primaire rijtaak veroorzaakte werklast en door allerlei andere zaken
veroorzaakte werklast, waaronder in-voertuig systemen. Variaties in werklast
ontstaan door al die elementen tezamen. Hoewel er verschillende methoden
bestaan voor het meten van de werklast ontbreekt een goede methode voor het
meten van variaties in de totale werklast. Het standaardarsenaal aan algemene
methoden voor het meten van de totale werklast bestaat uit (De Waard, 1994)<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l0 level1 lfo2; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]--><span style="font-family: "cg times"; mso-ansi-language: NL; mso-bidi-font-family: "CG Times"; mso-fareast-font-family: "CG Times";">1)<span style="font-family: "times new roman"; font-size: 7pt;"> </span></span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Zelf-rapportage maten,
zoals de NASA-TLX en de BSMI.<o:p></o:p></span></div>
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<!--[if !supportLists]--><span style="font-family: "cg times"; mso-ansi-language: NL; mso-bidi-font-family: "CG Times"; mso-fareast-font-family: "CG Times";">2)<span style="font-family: "times new roman"; font-size: 7pt;"> </span></span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Maten voor taakverrichting,
voor de primaire taak en voor secondaire taken.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l0 level1 lfo2; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]--><span style="font-family: "cg times"; mso-ansi-language: NL; mso-bidi-font-family: "CG Times"; mso-fareast-font-family: "CG Times";">3)<span style="font-family: "times new roman"; font-size: 7pt;"> </span></span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Fysiologische maten, zoals
de 0.10 Hz component van de hartslagvariabiliteit <o:p></o:p></span></div>
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<span style="font-family: "cg times"; mso-ansi-language: NL;">Met name de zelf-rapportage en de fysiologische maten
zijn voornameljk geschikt voor het meten van de werklast over een lange
periode, terwijl ze minder geschikt zijn vor het meten van kortdurende pieken
in de werklast. Secondaire taken worden voornamelijk toegepast ofwel om de
‘rest capaciteit’ te meten (bijv. Brown & Poulton, 1961) ofwel in het kader
van de multiple-resource theorie (Wickens, 1984). In beide gevallen gaat het
vaak om secondaire taken die gecontroleerde aandacht vragen en daardoor kunnen
interferen met de uitvoering van de primaire rijtaak. In het eerste geval wordt
er uitgegaan van een ongedifferentiëerde resource-pool waaruit zowel de
primaire als de secondaire taak putten. Als de secondaire taak een bepaalde
minimaal vereiste complexiteit heeft zal de taakprestatie daarop afnemen wanneer
de grenzen van de informatieverwerkingscapaciteit bereikt worden. In het tweede
geval, d.w.z. volgens de multiple-resource theorie, treedt er verslechtering op
van de secondaire taakprestatie wanneer zowel de primaire als de secondaire
taak gebruik maken van dezelfde resource. In dit model wordt ervan uitgegaan
dat er verschillende onafhankelijke resources zijn, zoals visueel, auditief en
manueel. Verwey (1991) vond in een experiment waarin dit model werd toegeast
dat een auditieve secondaire taak niet gevoelig was voor het meten van
verschillen in werkbelasting ten gevolge van de rij-situatie (rijden op een
snelweg, rotonde, op een oprit/afrit etc.), terwijl zowel een visuele detectie
als een visuele optel-taak dat wel waren. Een van de conclusies was dat de
verkeerssituatie een belangrijke determinant is van visuele werklast, en dat
daarom informatie niet visueel
gepresenteerd dient te worden.<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">In de tot dusver besproken benaderingen wordt ervan
uitgegaan dat je tijdens het rijden niet gedurende langere tijd naar iets
anders dan de weg kunt kijken en dat vooral visuele secondaire taken of visuele
in-voertuig systemen in tijd concurreren met de primaire rijtaak. Daardoor
neemt m.n. op visuele secondaire taken de taakprestatie af naarmate de noodzaak
om naar buiten te kijken toeneemt, of anders gezegd, wanneer de visuele
werklast t.g.v. de primaire taakcomplexiteit toeneemt. <o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Een andere mogelijk interessante benadering stelt dat bij
toenemende werklast de grootte van het functionele visuele veld afneemt. In dat
geval wordt er niet visueel aandacht besteedt volgens een alles-of-niets
principe, maar kan de veldgrootte waarin wordt waargenomen groeien of krimpen
al naar gelang de momentane werklast. Miura (1986) presenteerde tijdens een
wegexperiment lichtvlekken op de voorruit onder verschillende hoeken ten
opzichte van de bestuurder. De reactietijd voor het detecteren van deze
lichtvlekken werd gemeten. Het bleek dat tijdens het rijden in complexere
situaties met een grotere verkeersintensiteit het functionele visuele veld
kleiner werd, wat bleek uit een grotere reactietijd. De reactietijd nam toe
naarmate het functionele visuele veld kleiner werd. Soortgelijke effecten zijn
door Williams gerapporteerd (bijv.
Williams, 1985, 1995). Volgens Williams treedt er bij een toenemende visuele
(foveale) werklast een vorm van ‘tunnel visie’ op. Het vermogen om perifere
informatie te detecteren zou afnemen naarmate de foveale visuele werklast
toeneemt. <o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Deze benadering biedt perspectieven voor het meten van
momentane variaties in de werklast tijdens the autorijden, aangezien op elk
moment de grootte van het functionele visuele veld gemeten kan worden. In het
hierna besproken simulatorexperiment is een op deze benadering gebaseerde
methode onderzocht voor het meten van de werklast tijdens het autorijden. In
het experiment werden er tijdens het rijden waarschuwingen aan de bestuurder
gegeven wanneer deze volgens een gesimuleerd bestuurders
ondersteuningssysteem onveilig gedrag
vertoonde, d.w.z. te hard reed, te dicht volgde op een voorligger etc. Er
werden twee modaliteiten getest, nl. spraak boodschappen en tactiele
boodschappen. Beide doen volgens de multiple resource theorie niet een beroep
op visuele resources en zouden dus een lagere werklast moeten genereren dan visuele
boodschappen, hoewel het geven van aandacht aan de boodschappen nog steeds kan
leiden tot een toename van de werklast. Daarnaast kan het geven van
waarschuwingen leiden tot voorzichtiger gedrag van bestuurders waardoor er
beter geanticipeerd wordt op gevaarlijke en dus meer belastende situaties. In
dat geval zou het gebruik van het systeem op momenten waarop geen waarschuwing
gegeven wordt tot een lagere werklast kunnen leiden. <o:p></o:p></span></div>
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<br /></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">METHODE<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Apparatuur</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Het experiment werd
uitgevoerd in de moving-base rijsimulator van TNO-TM. Een gedetailleerde
beschrijving van deze simulator is te vinden in ….<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Proefpersonen</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Aan het experiment deden
60 proefpersonen mee variërend in leeftijd van 24 tot 50 jaar. Alle deelnemers
beschikten tenminste 5 jaar over het rijbewijs en reden minimaal 5000 km per
jaar. <o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Condities</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Iedereen voerde, na een
oefenrit, twee ritten uit van elk een half uur. De ene rit was op een
provinciale weg en de andere op een snelweg. De volgorde van wegtype werd
gebalanceerd tussen proefpersonen. Een derde van de deelnemers voerde de
controle ritten uit. Hierin werd er geen feedback (boodschappen) gegeven over
het rijgedrag, terwijl het ondersteuningssysteem wel boodschappen genereerde.
Deze werden echter gelogd in een bestand, maar niet aan de bestuurder
aangeboden. Een tweede groep van 20 proefpersonen kreeg spraak boodschappen
aangeboden. Bij deze waarschuwingen werd een ingesproken zin door de computer
aangeboden, zoals ‘pas op, u rijdt te hard, maximum snelheid 80’. Een derde
groep van 20 proefpersonen kreeg de waarschuwingen tactiel aangeboden. Daarbij
waren er twee soorten te onderscheiden, nl. een trilling op het stuurwiel als
waarschuwing om in de rijbaan te blijven, en een pulse op het gaspedaal als
waarschuwing om de snelheid aan te passen, bijvoorbeeld omdat de
snelheidslimiet overschreden werd of omdat een voorligger remde. Modaliteit was
dus een tussen-proefpersoonsfactor en wegtype een binnenproefpersoonsfactor.
Tegelijkertijd met de spraak en de tactiele boodschap werd de informatie ook op
een display aangeboden. Deze visuele informatie bestond uit een relevant
verkeersbord (bijv. een snelheidslimiet bord). Het display bood een extra
uitleg waar de bestuurder naar kon kijken wanneer deze daaraan behoefte had.
Het was echter niet nodig om naar het display te kijken. <o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Scenarios</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Tijdens de ritten werden
er verschillende scenarios opgeroepen die als functie hadden om systeem
activaties en dus waarschuwingen uit te lokken. Iedereen kreeg de volgende
scenarios aangeboden:<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Provinciale weg:<o:p></o:p></span></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Zes scherpe bochten. <o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Zes stopborden waarvoor een volledige stop moest worden gemaakt<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Voorligger die onverwacht remt.<o:p></o:p></span></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Langzaam rijdende voorligger die ingehaald moet worden<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Snelheidslimiet van 50 km/u<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Standaard was de snelheidslimiet 80 km/u, op een twee-baans weg met een
rijstrookbreedte van 3.1 m en een hoge verkeersdichtheid van het
tegemoetkomende verkeer.<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Snelweg:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Naderen van een file tijdens het rijden in mist.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Twee keer een voorligger die onverwacht remt.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Een inhalende auto die te kort invoegt.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Een pakje dat van een vrachtwagen valt.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Snelheidslimiet van 100 km/u.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 18.0pt; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: -18.0pt;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]--><span style="font-family: "cg times"; mso-ansi-language: NL;">Standaard was de snelheidslimiet 120 km/u, de rijstrookbreedte was 3.6 m en
er was een hoge dichtheid van het inhalende verkeer.<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Perifere
Detectie Taak (PDT)</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. Tijdens het rijden werd er op het scherm voor de bestuurder telkens een
klein rood vierkantje gedurende 1 s gepresenteerd. De proefpersoon diende
hierop te reageren door een micro-switch in te drukken dat bevestigd was om de
rechterwijsvinger. De reactietijd (RT) werd meten in ms. Wanneer er niet binnen
2 s een reactie kwam werd dit gecodeerd als een misser. Gemiddeld elke 4
seconden, met een random variatie tussen 3 en 5 s, werd deze stimulus
aangeboden onder een horizontale hoek van 11 tot 23 graden links van de lijn
tussen het hoofd van de bestuurder en de horizon, en 2 tot 4 graden boven de
horizon. De taak vraagt weinig bewuste aandacht en kan worden uitgevoerd zonder
het hoofd te bewegen. <o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<i><span style="font-family: "cg times"; mso-ansi-language: NL;">Data analyse</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">. De gemiddelde reactietijd
(RT) en de fractie missers, d.w.z. het aantal gemiste signalen gedeeld door het
aantal stimuli, werd berekend tijdens momenten waarop waarschuwingen gegeven
werden en op momenten dat er geen waarschuwing door het systeem gegeven werd.
Deze factor zal worden aangeduid met BOODSCHAP. Aangezien de spraak en de tactiele
conditie een verschillende waarschuwingsduur kennen, werd de periode waarin een
waarschuwing was gegeven gedefinieerd als het 10 s vanaf het moment dat de
boodschap begint. Dit was omdat de boodschap op het visuele display gedurende
10 s werd aangeboden. <o:p></o:p></span></div>
<span style="font-family: "cg times"; font-size: 10.0pt;"><br clear="all" style="page-break-before: always;" />
</span>
<br />
<div align="center" class="MsoNormal" style="text-align: center;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">RESULTATEN<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Figuur 1 geeft de resultaten op RT voor zowel de
provinciale weg (links) als de snelweg (rechts).<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi2Sh2zedHh4nGEOz1lIeeN2pPnAYn4LCWtXQbpakyg2aMUbitm2D0pYrz05npl8nj-B6V_L0h0Gne82fk9qdzsT3Kwdv9VClP6wRpBS8eXUsVcuCNx6O2421px6IFKvirfzBO2XJoVp2w/s1600/fig1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="236" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi2Sh2zedHh4nGEOz1lIeeN2pPnAYn4LCWtXQbpakyg2aMUbitm2D0pYrz05npl8nj-B6V_L0h0Gne82fk9qdzsT3Kwdv9VClP6wRpBS8eXUsVcuCNx6O2421px6IFKvirfzBO2XJoVp2w/s1600/fig1.jpg" width="320" /></a></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<br /></div>
<div class="MsoBodyText">
Figuur 1. Reactietijd op de
Perifere Detectie Taak als functie van wegtype, modaliteit en het moment (wel
of geen waarschuwing).</div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">De RT op de PDT werd tijdens de ritten op de provinciale
weg significant beïnvloedt door feedback modaliteit (F=7.37, p<.01) en door
of er wel of niet een waarschuwing werd gegeven: BOODSCHAP (F=45.27,
p<.001). Daarnaast was de interactie van feedback modaliteit x BOODSCHAP
statistisch significant (F=5.39, p<.01). Dit betekent dat het geven van
waarschuwingen resulteert in een toename van de werklast, met name tijdens de
waarschuwing zelf. Alleen het verschil tussen de controle conditie en de spraak
conditie was significant. Het geven van spraak boodschappen resulteert dus in
een hogere werklast. Tactiele waarschuwingen resulteren niet in een
significante toename van de werklast. Het patroon van de resultaten is
hetzelfde voor de snelweg. Ook hier werd de RT significant beïnvloedt door de
feedback modaliteit (F=12.26, p<.001) en de aanwezigheid van een
waarschuwing (F=132.87, p<.001). De interactie van feedback modaliteit x
BOODSCHAP was ook hier weer significant (F=16.03, p<.001). Ook tijdens de
ritten op de snelweg leidde het geven van een spraak boodschap dus tot een
momentane toename van de werklast.<o:p></o:p></span></div>
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<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">De fractie gemiste stimuli gaf een vergelijkbaar
resultaat, zie figuur 2. De fractie missers werd tijdens de ritten op de
provinciale weg significant beïnvloedt door feedback modaliteit (F=3.72,
p<.05). Daarnaast was de fractie gemiste stimuli significant groter wanneer
er een waarschuwing gegeven werd (F=45.27, p<.001). Evenals bij de RT was
ook de interactie tussen modaliteit en BOODSCHAP significant (F=5.37, p<.01).
De ritten op de snelweg geven hetzelfde beeld. De fractie gemiste stimuli werd
significant beïnvloedt door feedback modaliteit (F=3.36, p<.05) en door de
factor BOODSCHAP (F=129.58, p<.001). Daarnaast was de interactie feedback
modaliteit x BOODSCHAP weer statistisch significant (F=3.56, p<.05). <o:p></o:p></span></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhzAx54R_XQqamG6YWWCzfjEkm__mBBKjpgQAMhzzz97LDTvdKvUMljlIC9IG93JUHZVFVViDDyuBW-PS1TD-p2j6o_hvE9FwF49FW5m8ZJJqHfrSbaa7MWr2BdgTLNEmULw37hWq3CUEc/s1600/fig2.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="234" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhzAx54R_XQqamG6YWWCzfjEkm__mBBKjpgQAMhzzz97LDTvdKvUMljlIC9IG93JUHZVFVViDDyuBW-PS1TD-p2j6o_hvE9FwF49FW5m8ZJJqHfrSbaa7MWr2BdgTLNEmULw37hWq3CUEc/s1600/fig2.jpg" width="320" /></a></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Figuur2. Fractie gemiste stimuli op de Perifere Detectie
Taak als functie van wegtype, modaliteit en het moment (wel of geen
waarschuwing).<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">DISCUSSIE <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">De Perifere Detectie Taak blijkt een gevoelig instrument
voor het meten van kortdurende variaties in werklast en biedt een veelbelovende
methode voor het evalueren van de werklast ten gevolge van in-voertuig
systemen. Tactiele waarschuwingen verdienen de voorkeur boven gesproken
boodschappen aangezien de laatste resulteren in relatief grote toename van de
werklast. Waarschijnlijk wordt dit effect veroorzaakt doordat gesproken
boodschappen de bestuurder sterker afleiden. Bovendien duren gesproken
boodschappen langer dan tactiele boodschappen, waardoor de aandacht van de
bestuurder gedurende langere tijd in beslag wordt genomen. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">De hier gebruikte methode lijkt geschikt voor bredere
toepassingen waarin het evalueren van de werklast een rol speelt. Daarvoor
verdient het aanbeveling om de methode zodanig aan te passen dat deze niet hardware afhankelijk is van de hier gebruikte
testopzet. Tijdens het rijden in de simulator kijkt de bestuurder doorgaans
recht vooruit zodat het presenteren van de stimuli in een vast gebied op het
scherm geen problemen geeft. Voor praktijksituaties waarin de operator het
hoofd draait verdient het de voorkeur om over een hoofdbewegings-onafhankelijke
testinstrument te beschikken. De hier beschreven methode kan daarvoor geschikt
worden gemaakt.<o:p></o:p></span></div>
<span style="font-family: "cg times"; font-size: 10.0pt;"><br clear="all" style="page-break-before: always;" />
</span>
<br />
<div align="center" class="MsoNormal" style="text-align: center;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">REFERENTIES<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span style="font-family: "cg times"; mso-ansi-language: NL;">Brown, I.D.
& Poulton, E.C. (1961). </span><span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Measuring the spare ‘mental’ capacity of cardrivers by
a subsidiary task. <i>Ergonomics</i>, <i>4</i>, 35-40.<o:p></o:p></span></div>
<div class="MsoBodyText" style="margin-left: 36pt; text-indent: -36pt;">
<span lang="EN-GB">De Waard, D. (1996). <i>The measurement of drivers’ mental workload</i>.
PhD Thesis, University of Groningen.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Harms,
L. (1991). Experimental studies of variations in cognitive load and driving
speed in traffic and in driving simulation. In A.G. Gale, I.D. Brown, C.M.
Haslegrave, P. Smith & S. Taylor (eds.), <i>Proceedings of</i> <i>Vision in
Vehicles III</i>, (pp. 71-78). Amsterdam: Elsevier, North Holland. <o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Miura,
T. (1986). Coping with situational demands: A study of eye movements and
peripheral vision performance. In A.G. Gale, I.D. Brown, C.M. Haslegrave, P.
Smith & S. Taylor (eds.), <i>Proceedings
of</i> <i>Vision in Vehicles</i>, (pp.
205-216). Amsterdam: Elsevier, North Holland.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Rumar,
K. (1990). The basic driver error: late detection. <i>Ergonomics</i>, <i>33</i>,
1281-1290.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Verwey,
W.B. (1991). <i>Towards guidelines for
in-car information management: driver workload in specific driving situations</i>.
(Report IZF 1991 C13). Soesterberg, The Netherlands: TNO Institute for
perception.<o:p></o:p></span></div>
<div class="MsoBodyText" style="margin-left: 36pt; text-indent: -36pt;">
Verwey, W.B., Brookhuis, K.A. & Janssen, W.H. (1996). <i><span lang="EN-GB">Safety effects of in-vehicle information systems</span></i><span lang="EN-GB"> (Report TM-96-C002). Soesterberg,
The Netherlands: TNO Human Factors Research Institute.<o:p></o:p></span></div>
<div class="MsoBodyText" style="margin-left: 36pt; text-indent: -36pt;">
<span lang="EN-GB">Wickens, C.D. (1984). Processing
resources in attention. In R. Parasuraman & D.R. Davis (eds.) </span>Varieties
in attention. <span lang="EN-GB">(pp. 63-102).
London: Academic Press.<o:p></o:p></span></div>
<div class="MsoBodyText" style="margin-left: 36pt; text-indent: -36pt;">
<span lang="EN-GB">Wierwille, W.W.
(1993a). An initial model of visual sampling of in-car displays and controls. In
A.G. Gale, I.D. Brown, C.M. Haslegrave, P. Smith & S. Taylor (eds.), <i>Proceedings of</i> <i>Vision in Vehicles IV</i>, (pp. 271-280). Amsterdam: Elsevier, North
Holland.<o:p></o:p></span></div>
<div class="MsoBodyText" style="margin-left: 36pt; text-indent: -36pt;">
<span lang="EN-GB">Wierwille, W.W.
(1993b). Visual and manual demands of in-car controls and displays. In B.
Peacock & W. Karwowski (eds.), <i>Automotive
ergonomics</i> (pp. 299-320). London: Taylor & Francis.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Williams,
L.J. (1985). Tunnel vision induced by a foveal load manipulation. <i>Human Factors</i>, <i>27</i>, 221-227.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<span lang="EN-GB" style="font-family: "cg times"; mso-ansi-language: EN-GB;">Williams,
L.J. (1995). Peripheral target recognition and visual field narrowing in
aviators and nonaviators. </span><i><span style="font-family: "cg times"; mso-ansi-language: NL;">The International Journal
of Aviation Psychology</span></i><span style="font-family: "cg times"; mso-ansi-language: NL;">, <i>5</i>, 215-232.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 36.0pt; text-align: justify; text-indent: -36.0pt;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<br />
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "cg times"; mso-ansi-language: NL;"> <o:p></o:p></span></div>
DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-45432104382344356982014-06-15T06:06:00.001-07:002017-10-01T04:14:09.650-07:00Measuring drowsiness and impairment in car driving<div class="MsoBodyText2" style="text-indent: 14.2pt;">
<span lang="EN-US">The following is an unpublished article I made when I was working at the </span>TNO
Human Factors Research Institute. It concerns an experiment performed in a <a href="http://cs-driving-simulator.com/" target="_blank">car driving simulator</a> in 1999.</div>
<div class="MsoBodyText2" style="text-indent: 14.2pt;">
<span lang="EN-US"><br /></span></div>
<div class="MsoBodyText2" style="text-indent: 14.2pt;">
<span lang="EN-US">In a driving simulator the
effects of time-on-task were measured on variables that measure drowsiness,
driving performance and steering behaviour. It was found that the fraction of
time during which the eyes are closed is a good measure of drowsiness that is
sensitive to the effects of time-on-task. Of all single variables that measure
driver performance and impairment, the percentage of time during which any part
of the vehicle exceeded one of the lane boundaries was the most strongly
affected by time-on-task. Also, with progressing drowsiness, the amplitude of
steering corrections increased towards larger values. This was caused both by
larger error corrections in response to larger errors and by an increase in
coarseness of the steering response. Large steering corrections proved to be
the single best indicator of progressing impairment by drowsiness and fatigue. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<b><span lang="EN-US" style="font-size: 12.0pt; mso-bidi-font-size: 10.0pt;">1.
INTRODUCTION<o:p></o:p></span></b></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoBodyText" style="text-indent: 14.2pt;">
<span lang="EN-US">Falling
asleep at the wheel and drowsiness are considered important factors in accident
causation. Estimates of the involvement of these factors in accidents are
higher when the statistics are based on in-depth accident studies (10-25%)
compared to statistics based on general police databases (1-4%) (Horne &
Reyner, 1995). This indicates that, although the scope of the problem is not
clear, drowsiness and fatigue are significant risk factors. Because of this a
large number of studies on drowsiness, fatigue and sleepiness have been
reported in the literature. These studies differ widely in the variables used
to measure drowsiness and impaired driving. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">Drowsiness is a
psychophysiological state that is assumed to result in an inability of the
driver to drive safely. Drowsiness is often measured by eyelid closures. The
percentage of time the eyes of the driver are 80 to 100% closed (PERCLOS) has
been used as a variable for measuring drowsiness. Dingus, Hardee and Wierwille
(1987) found that PERCLOS correlated better with driver impairment than other
measures of eyelid closures that were examined. The use of eyelid closures as
an indicator of drowsiness stems from the general observation that as people
get drowsy they close their eyes more frequently and during longer periods,
until they finally fall asleep. However, in an experiment by Wierwille, Lewin
and Fairbanks (1996) it was found that PERCLOS did not predict drifting off the
road very well. Since measures of eyelid closure were not sensitive enough,
they advised to monitor lane position as well in order to detect driver
impairment. <o:p></o:p></span></div>
<div class="MsoBodyText" style="text-indent: 14.2pt;">
<span lang="EN-US">A
number of other studies have focussed on driver behaviour instead of driver
state. According to Bishop, Madnick, Walter and Sussman (1985), steering
activity becomes more coarse when driving for long periods of time: the number
of large steering movements increases while the number of smaller steering
amplitudes decreases. Seko, Kataoka and Senoo (1985) also found that with
reduced alertness caused by drowsiness, the number of steering corrections with
large amplitudes increases. This suggests that with progressing drowsiness the
number of lapses of attention increases resulting in longer periods during
which there are no steering corrections. This would result in drifting to the
edge of the lane which is corrected by a larger steering amplitude. This view
is consistent with the theory of ‘blocking’ as proposed by Bertelson and Joffe
(1963). They found that with progressing fatigue the occurrence of ‘blocks’ of
large reaction times increases. After a ‘block’, performance returns to normal
for a while. A blocking may express itself as a failure to commit a correcting
steering action in time which results in smaller safety margins to the lane
boundary, crossing the lane boundary or in moving off the road. In that case
the occurrence of an error (i.e. a smaller safety margin or a lane boundary
exceedance) is not the only indication of impaired performance because of
drowsiness. Also the increase in the number of large steering amplitudes is an
indication of error correction in response to a larger error. This error
correction response then evidences progressing impairment. Error correction may
then be defined as turning the steering wheel in the opposite direction, with a
large peak-to-peak amplitude, when the driver notices that the lane boundary is
about to be crossed or has been crossed. Error corrections prevent accidents to
occur and they may partly prevent effects of drowsiness on measures such as the
standard deviation of the lateral position (SDLP) or exceedance of the lane
boundaries. From this perspective it may be that effects on steering
amplitude-related measures as indicators of error correction show up earlier
than effects on lane position related variables. However, with progressing
drowsiness, error corrections may come too late resulting in increased swerving
or running off the road. <o:p></o:p></span></div>
<div class="MsoBodyText" style="text-indent: 14.2pt;">
<span lang="EN-US">This
reasoning assumes that safety margins to the lane boundary are perceived by the
driver and acted on by a correcting steering action. This principle has been
demonstrated by Godthelp (1988) in a study where drivers were instructed to
generate correcting steering actions when vehicle heading could still be
corrected comfortably to prevent a crossing of the lane boundary. Safety
margins were defined by the concept of Time-to-Line Crossing (TLC). This
represents the time available until any part of the vehicle reaches one of the
lane boundaries. This coupling of perception and action has also been
demonstrated for driving in curves by Van Winsum and Godthelp (1996) and for
the way drivers change lanes by Van Winsum (in press). <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">Another group of
studies has focussed on the effects of fatigue on driver performance instead of
psychophysiological measures and measures of driver control behaviour. The
standard deviation of the lateral position (SDLP) and exceedance of the lane
boundaries are generally referred to as indicators of the quality of driving
behaviour and, thus, driver performance. It has been found that SDLP increases
with time on task (Riemersma, Sanders, Wildervanck & Gaillard, 1977; De
Waard & Brookhuis, 1991). SDLP measures swerving and control over lateral
position. Another measure of driver performance is the proportion of time that
any part of the vehicle exceeds the lane boundary. This has been referred to as
‘LANEX’ by Wierwille, Lewin and Fairbanks (1996). LANEX is a strong indicator
of driver impairment. The minima of TLC are used in the present study as an
additional measure of driver performance. These minima represent the safety
margins to the lane boundaries that are maintained by the driver. Smaller TLC
minima indicate poorer lateral control and suggest poorer driver performance
and progressing impairment.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">In summary, three
types of variables are used in the present study. Variables that measure <i>driver performance</i> are LANEX, SDLP and
TLC minima. Other variables measure <i>drowsiness</i>.
These are related to eyelid closures, especially PERCLOS (i.e. the percentage
of time that both eyes are closed). The third type of variable relates to <i>driver behaviour</i> or more specifically to
steering behaviour of the driver. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The experiment
was performed in the driving simulator of the TNO Human Factors Research
Institute.<span style="font-size: small;"><o:p></o:p></span></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 18.0pt;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<b><span lang="EN-US" style="font-size: 12.0pt; mso-bidi-font-size: 10.0pt;">2.
METHOD<o:p></o:p></span></b></div>
<div class="MsoBodyText">
<br /></div>
<div class="MsoBodyText" style="text-indent: 14.2pt;">
<span lang="EN-US">Eighteen
paid subjects participated in the experiment. Age ranged between 24 and 70
years. All subjects had held their
drivers licence for more than 5 years and the annual kilometrage exceeded 5000
km. The experiment was performed in the driving simulator of the TNO Human
Factors Research Institute, described in detail in Hogema and Hoekstra (1998),
and Hoekstra, Van der Horst and Kaptein (1997).<o:p></o:p></span></div>
<div class="MsoBodyText">
<span lang="EN-US">For
the detection of eyelid closures, EOG was measured for both eyes with
electrodes attached just above and below each eye in line with the pupil. By
this procedure the signal is affected only by artefacts caused by vertical eye
movements and not by eye movements in the horizontal plane. The electrodes were
connected to a physiological amplifier with a timeconstant of 10 s. The
amplifier gave an output between –5 and +5 Volts. This was fed directly into
the A/D converter of the simulator computer, where it was sampled and stored
together with the driver behaviour data. This ensured a fixed synchronization
in time between all signals.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">All subjects were
informed about the purpose of the experiment and that it took three hours of
continuous driving. Subjects were free to stop driving at any moment without
negative consequences. They were requested to stop if they were feeling
uncomfortable or if they were too tired to continue to drive safely. After the
instructions, the electrodes for EOG measurement were attached and the signal
was tested with an oscilloscope. During the drive, speed was controlled by a
cruise control that was set at a constant speed of 80 km/h. This was expected
to facilitate the occurrence of drowsiness because of the relatively low speed
in a visually boring environment. All subjects drove continuously for three
hours during the daytime on a monotonous road under simulated evening lighting
conditions. No other traffic was encountered. The road was a standard two-lane
road with a lane width of 3.1 m, broken centerline and continuous edgelines. It
consisted of straight and curved segments with a continuous horizontal radius
of 2000 m that turned either to the left or to the right over an angle of 45º.
Subjects were instructed to drive in the right lane without exceeding the lane
boundaries. A mild side wind with varying force was simulated in order to
necessitate a minimum amount of steering effort. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">Coordinate
positions were stored as well as steering wheel angle, lateral position and EOG
recordings of both eyes with a frequency of 10 Hz. Time-to-Line Crossing (TLC)
was computed off-line according to the method described in Van Winsum,
Brookhuis and De Waard (in press). Time-on-task (TOT), i.e. the effect of
progressing time that is assumed to result in fatigue and drowsiness, was
treated as a within-subjects factor as follows. The first 20 minutes of each
run was not analyzed since this period was used to familiarize the subjects
with driving in the simulator. After this, the remaining time was divided into
5 sequential blocks of equal duration. Usually these blocks each covered a
period of 32 minutes. This means that there are 5 TOT blocks. Effects of
fatigue and drowsiness on task performance are expressed as an effect of TOT.
To evaluate time-on-task effects the dependent variables were averaged over
each block and divided by the average value for the first block where
appropriate. In this way all variables have the same units and can be compared
directly in terms of the sensitivity to TOT effects. If it is assumed that
drowsiness increases with increasing time on task, then the variables with the
strongest statistical effect of TOT are most useful as indicators of
drowsiness. This procedure of dividing the average by the data of the first
time block can only be used if the data on the first block can never be zero.
Therefore, not all variables are suitable for treatment by this procedure. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">EOG data were
filtered off-line and the filtered signal was subtracted from the raw EOG
signal to allow peak detection analysis by a computer program that detected
eyeblinks and eyelid closures. These were transformed into the following
indicators of drowsiness:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l3 level1 lfo4; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">PERCLOS, i.e. the fraction of time during which both
eyes are closed<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l3 level1 lfo4; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">BLINK, i.e. the blinkfrequency<o:p></o:p></span></div>
<div class="MsoBodyText2">
<span lang="EN-US">For each TOT block, the average value was
divided by the value of the first block.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The following
indicators of driver performance were computed:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">LANEX, i.e. the fraction of time during which any of
the wheels exceeds the right lane boundary.<o:p></o:p></span></div>
<div class="MsoEndnoteText" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">SDLP, i.e. the standard deviation of lateral position,
with respect to the first block.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">TLC minima to the left and
right lane boundaries were determined and only minima of less than 20 s were
analyzed. These minima were used to compute:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">TLC<sub>1.0</sub>, i.e. the percentage of TLC minima
smaller than 1.0 s.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The following
indicators of steering behaviour were computed:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">SDST, i.e. the standard deviation of steering wheel angle,
with respect to the first block,<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">P3-6, i.e. the power of fast steering movements (in
the domain of 0.3-0.6 Hz) as a fraction of all steering activity < 0.6 Hz,
with respect to the first block. <o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">STAMP, i.e. the average of peak-to-peak steering
amplitudes, with respect to the first block,<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l1 level1 lfo1; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">-
</span><!--[endif]--><span lang="EN-US">STDIS, i.e. the fraction of larger peak-to-peak
steering amplitudes. This was computed as follows: for the first block the
distribution of all peak-to-peak steering amplitudes was computed and the 80<sup>th</sup>
percentile value (i.e. that value for which 80% of all values are smaller and
20% of all values are larger) was determined. Then, for all subsequent time
blocks the percentage of values that was larger than the initial 80<sup>th</sup>
percentile value was computed and divided by 20 (i.e. the percentage larger
than the value in the first block). Figure 1 gives a graphical illustration of
this principle. There are two bell-shaped distributions of peak-to-peak
steering amplitudes. The left distribution refers to the first block, while the
right distribution represents block i. The idea then is that as drowsiness
progresses, the distribution of steering amplitudes shifts towards larger
values (to the right). The vertical line represents the value of steering
amplitudes, during the first block, that separates the 20% largest values from
the 80% lowest values. The sum of the striped and black area represents the
percentage of values that is larger than P80 of the first block. STDIS then is
the sum of the black and striped area divided by the black area. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The following
types of analyses were conducted:<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 0cm; mso-list: l0 level1 lfo2; tab-stops: list 18.0pt; text-align: justify; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">1)
</span><!--[endif]--><span lang="EN-US">The effect of time on task was tested with analysis
of variance using a within-subjects repeated measurement design. The aim of
these analyses was to evaluate the relative sensitivity of the dependent
variables to effects of drowsiness.<o:p></o:p></span></div>
<div class="MsoEndnoteText" style="margin-left: 0cm; mso-list: l0 level1 lfo2; tab-stops: list 18.0pt; text-indent: 0cm;">
<!--[if !supportLists]--><span lang="EN-US">2) </span><!--[endif]--><span lang="EN-US">For
each block the magnitude of the TLC minima was related to the correcting
steering wheel action in the opposite direction. This was realized as follows.
TLC minima to the right lane boundary result in a path-correcting turning of
the steering wheel to the left, while TLC minima to the left lane boundary
result in a path-correcting turning of the steering wheel to the right. All TLC
minima to either the left or the right were detected together with the accompanying
correcting peak-to-peak steering amplitude to the opposite direction. Then the
TLC minima were categorized into groups according to the magnitude of the TLC
minima. For testing the relation between TLC minima and steering corrections,
the following groups were distinguished:<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1 =TLC minima >0.0 and <=1.5 s; 2 =TLC minima >1.5 and <=3.0 s<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">3 =TLC minima >3.0 and <=4.5 s; 4 =TLC minima >4.5 and <=6.0 s<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">5 =TLC minima >6.0 and <=7.5 s; 6 =TLC minima >7.5 and <=9.0 s<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">7 =TLC minima >9.0 and <=10.5 s; 8 =TLC minima >10.5 and <=12.0 s<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">9 =TLC minima >12.0 and <=13.5 s; 10 =TLC
minima >13.5 and <=15.0 s<o:p></o:p></span></div>
<div class="MsoBodyTextIndent" style="margin-left: 0cm; text-indent: 0cm;">
<span lang="EN-US">A smaller TLC minimum can be considered as a
larger error that is compensated by a larger steering correction (larger
peak-to-peak steering amplitude in the opposite direction). Analyses of
variance were applied to test whether the sensitivity of the steering response
to TLC information changes as a function of time on task.<span style="font-size: small;"><o:p></o:p></span></span></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-CrZCrwLsD1hz3jf5x9qg2dijH3yEqSEex36KAKiX3QYfIoBzGVRHrzj-lv-PRe86JJrzSr_ykdjV2GRV5RNTuzBTzHVRLl2YNa7RznnVhYLYAjSQ6zvN0u197_Mv38-fvWNzeY_PiPM/s1600/fig1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-CrZCrwLsD1hz3jf5x9qg2dijH3yEqSEex36KAKiX3QYfIoBzGVRHrzj-lv-PRe86JJrzSr_ykdjV2GRV5RNTuzBTzHVRLl2YNa7RznnVhYLYAjSQ6zvN0u197_Mv38-fvWNzeY_PiPM/s1600/fig1.jpg" width="320" /></a></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<br /></div>
<div class="MsoBodyText2">
<span lang="EN-US">Figure 1. Distributions of peak-to-peak
steering amplitudes. STDIS is computed as the sum of the black and striped area
divided by the black area. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<b><span lang="EN-US" style="font-size: 12pt;"><br clear="all" style="page-break-before: always;" />
</span></b>
<br />
<h3 style="margin-left: 18pt; text-indent: -18pt;">
<!--[if !supportLists]--><span lang="EN-US">3.<span style="font-size: 7pt; font-weight: normal;"> </span></span><!--[endif]--><span lang="EN-US">RESULTS<o:p></o:p></span></h3>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">Table 1 gives an
overview of the effects of time on task on the different dependent variables.
It can be seen that all variables related to driver performance, drowsiness and
steering behaviour are strongly affected by time of driving: performance
deteriorates with increased driving time, and drivers become more drowsy while
their steering becomes more coarse. The steering amplitude related variables,
i.e. STDIS and STAMP, have the largest effect of time on task. This means that
the effect of time-on-task on these variables is the most reliable, as
indicated by the F-statistic. When comparing STDIS and STAMP, the effect size
of time-on-task is the largest for STDIS. This can also be seen in figure 2.
These results indicate that, of all variables examined in the present
experiment, the fraction of large peak-to-peak steering amplitudes (STDIS) is
the best indicator of drowsiness-related driving impairment.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoBodyText2">
<span lang="EN-US">Table 1. Effects of time on task on the
dependent variables (F-statistics), together with average values<o:p></o:p></span></div>
<table border="1" cellpadding="0" cellspacing="0" class="MsoNormalTable" style="border-collapse: collapse; border: none; mso-border-bottom-alt: solid green 1.5pt; mso-border-insideh: cell-none; mso-border-insidev: cell-none; mso-border-top-alt: solid green 1.5pt; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-table-layout-alt: fixed; mso-yfti-tbllook: 175;">
<tbody>
<tr>
<td colspan="3" style="border-bottom: solid green 1.0pt; border-left: none; border-right: none; border-top: solid green 1.5pt; mso-border-bottom-alt: solid green .75pt; mso-border-top-alt: solid green 1.5pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 237.6pt;" valign="top" width="396"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td colspan="5" style="border-bottom: solid green 1.0pt; border-left: none; border-right: none; border-top: solid green 1.5pt; mso-border-bottom-alt: solid green .75pt; mso-border-top-alt: solid green 1.5pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 180.0pt;" valign="top" width="300"><div align="center" class="MsoNormal" style="text-align: center;">
<span lang="EN-US">Time on task block<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal">
<span lang="EN-US">Type<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal">
<span lang="EN-US">Dependent variable<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal">
<span lang="EN-US">Effect of time on task df=68,4<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal">
<span lang="EN-US">1<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal">
<span lang="EN-US">2<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal">
<span lang="EN-US">3<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal">
<span lang="EN-US">4<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.0pt; border: none; mso-border-bottom-alt: solid green .75pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal">
<span lang="EN-US">5<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<i><span lang="EN-US">Driver
performance<o:p></o:p></span></i></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">LANEX<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">8.81 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">0.02<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">0.05<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">0.06<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">0.08<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">0.08<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">TLC<sub>1.0</sub><o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">7.34 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">4.48<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">6.33<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">6.14<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">6.78<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">7.14<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">SDLP relative<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">8.30 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.17<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.29<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.31<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.38<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><h6>
<span lang="EN-US" style="font-size: small;">Drowsiness</span></h6>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">PERCLOS<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">5.90 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.24<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.63<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.91<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">2.14<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">BLINK<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">9.51 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.20<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.43<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.48<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.58<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<i><span lang="EN-US">Steering
behaviour<o:p></o:p></span></i></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">STDIS<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">14.60 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.0<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.38<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.62<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.77<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.83<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">STAMP<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">15.25 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.09<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.18<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.22<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.25<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">SDST<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">11.49 **<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.09<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.11<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.20<o:p></o:p></span></div>
</td>
<td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.20<o:p></o:p></span></div>
</td>
</tr>
<tr>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<br /></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">P3_6<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 79.2pt;" valign="top" width="132"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">9.00 **<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.00<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.04<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.08<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.13<o:p></o:p></span></div>
</td>
<td style="border-bottom: solid green 1.5pt; border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 36.0pt;" valign="top" width="60"><div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">1.12<o:p></o:p></span></div>
</td>
</tr>
</tbody></table>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">** <i>p</i> < .001<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoBodyText" style="text-indent: 14.2pt;">
<span lang="EN-US">From
the previous analyses it appeared that with progressing drowsiness driver
errors increased which resulted in more frequent crossing of the lane
boundaries and smaller TLC minima. This may explain the shifting to larger
steering corrections with time-on-task, since larger errors may be corrected by
larger corrections. In order to test this, the magnitude of the TLC minima was
related to the correcting steering wheel action in the opposite direction for
each block according to the procedure described in paragraph 2. Analyses of
variance were applied to test whether the sensitivity of the steering response
to TLC information changes as a function of time on task. In these analyses the
time-on-task effects of block 1 vs block 5 were tested. The effect of
time-on-task on the amplitude of the steering corrections was significant
(F(17,1)=30.43, p<.001), while the effect of TLC minimum on the amplitude of
the corrective steering actions was significant as well (F(153, 9)=135.89,
p<.001). This is illustrated in figure 3.<span style="font-size: small;"><o:p></o:p></span></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFTrR7t2BS4zFZBJYImdq1R1ULLilUMaPDe-w59e8dmKq8vjrFCqXd3F4RTbxL5-C8p_I4nqU8Ec4D_OEue-yXHTo-A8nzkH2ryEYTneAOHlgtJFHIFofbBJsStOm83SpGD_K0ovtlCo0/s1600/fig2.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFTrR7t2BS4zFZBJYImdq1R1ULLilUMaPDe-w59e8dmKq8vjrFCqXd3F4RTbxL5-C8p_I4nqU8Ec4D_OEue-yXHTo-A8nzkH2ryEYTneAOHlgtJFHIFofbBJsStOm83SpGD_K0ovtlCo0/s1600/fig2.jpg" width="292" /></a></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<br /></div>
<div class="MsoBodyText2">
<span lang="EN-US">Figure 2. Variables related to steering
behaviour as a function of time on task.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The results show
that the magnitude of the correcting steering action is strongly related to the
magnitude of the error, since smaller TLC minima are associated with larger
correction peak-to-peak steering amplitudes in the opposite direction. However,
in addition the effect of time-on-task of steering amplitude is highly
significant, despite the fact that it has been controlled for TLC minima. This
means that although the increase in larger steering corrections with
time-on-task can partly be explained by the increase in errors (small TLC minima)
with progressing time-on-task, there still is a substantial increase in the
magnitude of peak-to-peak steering corrections which cannot be explained by
larger errors. This suggests that as drowsiness increases, steering reactions
to a movement of the car towards the lane boundaries become larger.<span style="font-size: small;"><o:p></o:p></span></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJQJ8zJ90ZMhwSS0r4MCl_jvFDghJ4-haVA6HgZPMpYm0roAC7m3MD0Y_IBs_37pIUQcJ1mh6Hx7B635vixRVKyIGNtv3EvqxqO1ZOU3ZOdiyTTmGpgCRjUY82iPu6XJQBIoVFqi4_D_A/s1600/fig3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJQJ8zJ90ZMhwSS0r4MCl_jvFDghJ4-haVA6HgZPMpYm0roAC7m3MD0Y_IBs_37pIUQcJ1mh6Hx7B635vixRVKyIGNtv3EvqxqO1ZOU3ZOdiyTTmGpgCRjUY82iPu6XJQBIoVFqi4_D_A/s1600/fig3.jpg" width="294" /></a></div>
<div align="center" class="MsoNormal" style="text-align: center;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="text-align: justify;">
<span lang="EN-US">Figure 3. Peak-to-peak
steering amplitude as a function of TLC minima for the first and the last
time-on-task blocks.<span style="font-size: small;"><o:p></o:p></span></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoEndnoteText">
<br /></div>
<h3 style="margin-left: 18pt; text-indent: -18pt;">
<!--[if !supportLists]--><span lang="EN-US">4.<span style="font-size: 7pt; font-weight: normal;"> </span></span><!--[endif]--><span lang="EN-US">CONCLUSIONS AND DISCUSSION<o:p></o:p></span></h3>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">In an experiment
performed in the TNO driving simulator the effects of drowsiness on several
measures of driving performance, drowsiness and steering behaviour were
studied. The method used was prolonged driving under monotonous environmental
conditions. The results reveal significant effects of time-on-task on variables
that measure drowsiness. These variables were based on eyelid closures derived
from EOG measurements. Both the fractions of time during which both eyes were
closed (PERCLOS) and the frequency of eyeblinks (BLINK) were significantly
affected by time-on-task. This suggests that the experimental setup resulted in
the desired effect of inducing drowsiness in the subjects. In accordance with
the literature, PERCLOS appears to be a valid indicator of drowsiness. This
variable is easy to compute from the data of an eyelid monitor and may be a
useful variable for driving impairment detection systems. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 18.0pt;">
<span lang="EN-US">Driver
performance was measured by means of variables that were derived from lateral
position. Of all performance-related variables, the fraction of time during
which any part of the vehicle exceeds one of the lane boundaries (LANEX) was
the most sensitive to effects of time-on-task. Because of this, it is
recommended to include this variable in systems that are aimed at driver
impairment detection. Also, in accordance with the literature, the standard
deviation of lateral position (SDLP) was significantly affected by time-on-task
as were the TLC minima.<o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 14.2pt;">
<span lang="EN-US">The results of
the steering related variables show that the fraction of large peak-to-peak
steering amplitudes that are larger than the 80<sup>th</sup> percentile value
during the initial period of driving were the most sensitive to the effects of
time-on-task. This indicates that the distribution of steering amplitudes
shifts towards larger values with progressing time. This variable appears to be
more sensitive than all other variables that were measured in this experiment,
driver performance and drowsiness-related variables included. It is therefore
recommended to include this variable in systems for detecting drowsiness-related
driver impairment. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify; text-indent: 18.0pt;">
<span lang="EN-US">In a final
analysis it was evaluated how the relation between the magnitude of the errors,
measured by the TLC minima, and the magnitude of the correcting steering wheel
movements to the opposite direction was affected by time-on-task. The shift to
larger steering corrections with progressing time-on-task may partly be
explained by the larger errors that are committed when drowsiness increases. It
appeared that the amplitude of the correcting steering response is indeed
strongly related to the momentary TLC minimum: a smaller TLC minimum is
accompanied by a larger steering correction in the opposite direction. However,
when corrected for the level of the TLC minima, steering corrections still
increase significantly with time-on-task. This cannot be explained by larger
errors with progressing fatigue. The results suggest that the larger steering
corrections that occur with higher levels of drowsiness are both the result of
larger errors and of increased coarseness of the steering responses. The
mechanism responsible for this effect is unclear. A possible explanation may be
that with progressing drowsiness drivers tend to look at a point on the road
closer in front in an attempt to reduce visual input. This may then result in
poorer lateral control. There is experimental evidence for the idea that
lateral control performance deteriorates when the driver has less preview, as
is the case when the driver looks at a point closer in front of the vehicle.
For example, Tenkink (1988) studied the effects of sight distances of 27, 37
and 183 meters on lateral control performance. He found that a smaller sight
distance resulted in a larger SDLP at a given speed. The hypothesis that drowsy
drivers look at a point closer in front of the vehicle is consistent with the
results of Kaluger and Smith (1970). They found, in a study of driver fatigue,
that drivers looked closer in front of the vehicle after several hours of
driving. Mourant and Rockwell (1972) have described this compensating strategy
of fatigued drivers as a regression towards the visual scan behaviour of novice
drivers, who also are characterized by looking closer in front of the car
compared to experienced drivers. Alternatively, this change in visual scanning
strategy may be an attempt to reduce the amount and complexity of visual input.
However, this hypothesis needs to be tested in further research. <o:p></o:p></span></div>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<h2>
<span lang="EN-US" style="font-size: small; font-weight: normal;">REFERENCES<o:p></o:p></span></h2>
<div class="MsoNormal" style="text-align: justify;">
<br /></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Bertelson,
P. & Joffe, R. (1963). Blocking in prolonged serial responding. Ergonomics,
6, 109-116.<o:p></o:p></span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
<span lang="EN-US">Bishop, H., Madnick, B., Walter, R. & Sussman, E.D. (1985).
Potential of driver attention monitoring system development (Report DOT HS 806
744). Springfield, VA: National Highway Traffic Safety Administration.</span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Dingus,
T.A., Hardee, L. & Wierwille, W.W. (1987). Development of models for
on-board detection of driver impairment. Accident Analysis and Prevention,
19(4), 271-283.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Godthelp,
J. (1988). The limits of path error-neglecting in straight lane driving. </span>Human
Factors, 28, 211-221.<o:p></o:p></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
Hoekstra, W. van der Horst, R. & Kaptein, N.A. (1997). <span lang="EN-US">Visualisation of
road design for assessing human factors aspects in a driving simulator.
Proceedings Driving Simulator Conference (DSC ’97), 8-9 September, Lyon,
France.<o:p></o:p></span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
<span lang="EN-US">Hogema, J.H. & Hoekstra, W. (1998). Description of the TNO
Driving Simulator (Report TM-98-D007). Soesterberg, The Netherlands: TNO Human
Factor Research Institute.</span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Horne,
J.A. & Reyner, L.A. (1995). Sleep related vehicle accidents. British
Medical Journal, 310, 565-567.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Kaluger,
N.A. & Smith, G.L. (1970). Driver eye-movement patterns under conditions of
prolonged driving and sleep deprivation. Highway Research Record.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Mourant,
R.R & Rockwell, T.H. (1972). Strategies of visual search by novice and
experienced drivers. Human Factors, 14, 325-335.<o:p></o:p></span></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
<span lang="EN-US">Riemersma,
J.B.J., Sanders, A.F., Wildervanck, C. & Gaillard, A.W. (1977). Performance
decrement during prolonged night driving. In R.R. Mackie (Ed.), Viligance:
Theory, operational performance and physiological correlates (pp. 41-58). New
York: Plenum.<o:p></o:p></span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
<span lang="EN-US">Seko, Y., Kataoka, S. & Senoo, T. (1985). Analysis of driving
behavior under a state of reduced alertness. JSAE Review, April, 66-72.</span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
<span lang="EN-US">Tenkink, E. (1988). Lane keeping and speed choice with restricted
sight distances. In T. Rothengatter & R. de Bruin (Eds.). Road user
behaviour: theory and research. </span>Assen/Maastricht,
The Netherlands: Van Gorkum<o:p></o:p></div>
<div class="MsoNormal" style="margin-left: 14.2pt; text-align: justify; text-indent: -14.2pt;">
Waard, D. de & Brookhuis. <span lang="EN-US">K.A. (1991). Assessing driver status: a
demonstration experiment on the road. Accident Analysis and Prevention, 23(4),
297-307.<o:p></o:p></span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
<span lang="EN-US">Wierwille, W.W., Lewin, M.G. & Fairbanks, R.J. (1996). Research
on vehicle-based driver status.performance monitoring, PART III (Report DOT HS
808 640). Springfield, VA: National Highway Traffic Safety Administration.</span></div>
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<span lang="EN-US">Winsum,
W. van & Godthelp, H. (1996). Speed choice and steering behaviour in curve
driving, Human Factors, 38(3), 434-441.<o:p></o:p></span></div>
<div class="MsoBodyTextIndent3" style="margin-left: 14.2pt; text-indent: -14.2pt;">
Winsum, W. van, Brookhuis, K.A. & Waard, D.
de. <span lang="EN-US">(in press). A comparison of different ways to
approximate time-to-line crossing (TLC) during car driving. Accident Analysis
and Prevention. </span></div>
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<span lang="EN-US">Winsum,
W. van (in press). Lane change manoeuvres and safety margins. Transportation
Research, Part F: Traffic Psychology and Behaviour.<o:p></o:p></span></div>
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DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-62326333684369544362014-06-08T04:37:00.000-07:002017-10-01T04:14:30.103-07:00How alcohol affects driving<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEho11OkV5B0rF_FDGrGXhD80haAUcS6qt60p55p3Juh1vSH20Bn-iUsuLPK4gFb5h2kw7ekU1wlq-pLaEWwyakNQt5sJNr2O1PChHQ83Bxu-8O-Ocy0ngj3J55gkG_CNbZnK1AOmUIW5FE/s1600/drinking-and-driving.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEho11OkV5B0rF_FDGrGXhD80haAUcS6qt60p55p3Juh1vSH20Bn-iUsuLPK4gFb5h2kw7ekU1wlq-pLaEWwyakNQt5sJNr2O1PChHQ83Bxu-8O-Ocy0ngj3J55gkG_CNbZnK1AOmUIW5FE/s1600/drinking-and-driving.jpg" width="314" /></a></div>
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<span style="font-family: "times new roman" , serif; font-size: 12pt;">Alcohol is
one of the most important factors in accident causation while driving. It is
involved in over 25% of all car crashes in the US and a number of European
countries. Most accidents occur with young male drivers. They are inexperienced
and generally overestimate their driving skills and underestimate the effects
of alcohol. An additional problem is that people under 20 often don’t ‘feel’
the effects of alcohol which causes them to drink much more than others.</span><br />
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<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">The effects of alcohol on driving behaviour can be summarized as</span></span></div>
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</span><span style="font-family: "times new roman" , serif; font-size: 12pt;"></span>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">- Alcohol affects skills required for safe driving and results in poorer
steering control and choice of higher driving speeds</span></span></div>
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</span><span style="font-family: "times new roman" , serif; font-size: 12pt;"></span>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">- Young drivers are often not aware of the dangerous effects of alcohol on
driving performance</span></span></div>
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</span><span style="font-family: "times new roman" , serif; font-size: 12pt;"></span>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">- Because of this, they don't compensate for the negative effects by driving
more carefully, or by a lower speed choice or by investing more effort in the
driving task.</span></span><br />
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</span>
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<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">This lack of awareness and of compensation results in a dramatically increased
accident risk.</span></span></div>
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</span><span style="font-family: "times new roman" , serif; font-size: 12pt;"></span>
<br />
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<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">Participating in a simulation of the effects of alcohol on driving performance
in a driving simulator can be an eye opener for this group. I hope this results
fewer DUI accidents in young drivers.</span></span></div>
<span style="font-family: "times new roman" , serif; font-size: 12pt;"></span><br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt;"><span style="font-size: 12pt;">More details on </span><a href="http://cs-driving-simulator.com/" target="_blank"><span style="color: #2b5fc6; font-family: "times new roman" , "serif"; font-size: 12.0pt;">the effects of alcohol on driving and the use of a car driving simulator can be found here.</span></a></span></div>
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</span>DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-77165856322568779462014-06-08T04:32:00.000-07:002017-12-09T08:05:33.488-08:00Accident risk of young drivers<div class="MsoNormal" style="margin-bottom: 0.0001pt;">
<span style="font-family: "times new roman" , "serif"; font-size: 12.0pt;">Young
drivers between 18 and 24, especially males, are much more often involved in
accidents in comparison to drivers of other age groups. This is one of the most
consistently observed phenomena in traffic throughout the world. Young drivers
are also the least experienced. The reason for the high involvement of young
drivers in vehicle accidents is not clear, even when exposure to risk is
controlled for. While young people from 16 to 24 years of age represent 17% of
the Canadian population, they account for 58% of all driver fatalities in
Canada! <o:p></o:p></span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidol7f0ASy2ZG5tmJYPvOGDU4owAkh-z5fp1VR89Bb0-exeEDoEAl0jUe1r2D1wfLYPUyL7_5uQToVYCcjyxCbVd4fBmOrHlBB_ZsJRND33Ecwb279yoflklCL4u7Tw2CBkzTScP5X0_M/s1600/young-driver.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="200" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidol7f0ASy2ZG5tmJYPvOGDU4owAkh-z5fp1VR89Bb0-exeEDoEAl0jUe1r2D1wfLYPUyL7_5uQToVYCcjyxCbVd4fBmOrHlBB_ZsJRND33Ecwb279yoflklCL4u7Tw2CBkzTScP5X0_M/s1600/young-driver.jpg" width="320" /></a></div>
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<span style="font-family: inherit; font-size: 12.0pt;">Poorer risk
perception is often proposed as the cause for the high accident involvement of
young driver. It has been stated that, even though young drivers may perceive
as much risk while driving as older drivers and thus do not deliberately seek
more risk, they may be more confident in their ability to avoid an accident.</span></div>
<div style="text-align: justify;">
<span style="font-family: inherit; font-size: 12.0pt;">
In a number of studies, young drivers gave lower ratings of accident risk for
driving situations which demanded fast reflexes or substantial vehicle handling
skills. They rated their own risk of an accident and driving abilities as being
the same as for older drivers. However, they saw their peers as being
significantly more at risk and as having poorer abilities than themselves. The
data suggested that risk perception is strongly related to perceived ability.
In another study it was found that drivers with three years of experience
judged themselves to have better driving skills compared to other drivers. The
drivers who gave the highest ratings on skill also reported faster driving.</span><br />
<span style="font-family: inherit; font-size: 12.0pt;"><br /></span>
<span style="font-family: inherit; line-height: 115%;">In another line or research, the high accident involvement rate of especially
young male drivers has been associated with the use of alcohol and drugs as a
lifestyle-related phenomenon. Although as many as 50% of fatally injured young
drivers have been found to be positive for alcohol, this is slightly lower than
the frequency for older drivers. Also, it has become clear from surveys that
drinking and driving is widespread among younger drivers although they had
typically consumed less alcohol than older drivers. In alcohol related crashes
younger drivers tend to have lower BACs than older drivers. Yet, the high
accident involvement among young drivers has been attributed to risky driving behaviour
as an aspect of adolescent lifestyle that is embedded in the same set of
personality and behaviour aspects as other kinds of adolescent problem
behaviour such as delinquency, problem drinking and illegal drug use and
smoking. Some authors believe that the high accident involvement of young, and
especially male, drivers is a lifestyle related phenomenon resulting in a
higher deliberate risk acceptance or higher target level of risk. But in that
case it would be expected that a higher percentage of accident involved young
drivers are positive on alcohol and have higher BAC levels compared to older
drivers. This obviously is not the case.</span></div>
</div>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , serif; font-size: 12pt; line-height: 115%;">It has frequently been reported that the relative risk of becoming involved in
a fatal accident rises faster as a function of BAC level for younger drivers
compared to older drivers. In other words, with increases in the amount of
alcohol consumed, the accident risk increases for all age groups, but much more
rapidly for the young. Although the reason for the interaction between age and
BAC level on accident involvement is not clear, it suggests that both factors
share a common locus of effect, in the sense that the factor that causes the
higher accident rate of young drivers is aggravated by alcohol. In the discussion
of the effects of alcohol it was suggested that the lack of compensation for
impaired performance may be the cause for the large role of alcohol in accident
causation. Evidence was presented that drivers are unaware of performance
decrements under alcohol which is possibly the cause for the absence of
compensatory speed changes and effort. From the same perspective it may be
suggested that young and inexperienced drivers have not yet learned to
recognize the effects of situational factors on their performance and thus fail
to compensate for these effects resulting in speeds that are too high for the
circumstances. Extensive practice on relevant driving tasks can be improved in
driver training and a driving simulator can be a useful tool to accomplish that.</span><br />
<span style="font-family: "times new roman" , serif; font-size: 12pt; line-height: 115%;"><br /></span>
<span style="font-family: "times new roman" , serif; font-size: 12pt; line-height: 115%;">Other examples of <a href="http://www.bizycart.com/" target="_blank">traffic psychological theories and models</a> can be found here. </span></div>
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</span>
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<span style="font-family: "times new roman" , "serif";"><span style="line-height: 18.399999618530273px;"><br /></span></span></div>
<span style="font-family: "times new roman" , "serif";">
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<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt; line-height: 115%;"><span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt; line-height: 115%;">More details on </span></span><span style="font-family: "calibri" , "sans-serif"; font-size: 11pt; line-height: 115%;"><span style="color: #2b5fc6; font-family: "times new roman" , "serif"; font-size: 12.0pt; line-height: 115%;"><a href="http://cs-driving-simulator.com/" target="_blank">the accident risk of young drivers and how to use a car driving simulator can be found here</a>.</span></span></span></span></div>
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt; line-height: 115%;">
</span></span>DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0tag:blogger.com,1999:blog-7425052451805457771.post-12568800845159292272014-06-08T04:26:00.001-07:002017-10-01T04:15:04.210-07:00Does a better car result in safer driving ?<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjIwXyJnJHIHF4JXlR7NQaTsU56dbinQImwK98YLV7JnLDx-aphqR_rjR3aGK9_YoAocQ-qTae-LHLU5QTLYJzYrUO33Eynn_OCvsiEtUJIQRpLw-Zl4RkzYnTvM8TrBetGxJ1nIxMZsV8/s1600/powercar.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjIwXyJnJHIHF4JXlR7NQaTsU56dbinQImwK98YLV7JnLDx-aphqR_rjR3aGK9_YoAocQ-qTae-LHLU5QTLYJzYrUO33Eynn_OCvsiEtUJIQRpLw-Zl4RkzYnTvM8TrBetGxJ1nIxMZsV8/s1600/powercar.jpg" /></a></div>
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<span style="font-family: "times new roman" , serif; font-size: 12pt;">It is often
assumed that better cars result in safer driving and fewer accidents. Although
this seems to make sense, the reality is that people adapt their behaviour to
vehicle characteristics. For example, if a car accelerates better, the driver
often accepts smaller safety margins. If the brake system of the car is better,
drivers may follow a lead vehicle with a smaller headway.</span></div>
<span style="font-family: "times new roman" , "serif";"></span><br />
<div style="text-align: justify;">
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<span style="font-family: "times new roman" , "serif";">
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<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;"><span style="font-family: "times new roman" , serif; font-size: 12pt;">A number of studies have revealed effects of vehicle characteristics on
tactical driver behaviour. Tactical driver behaviour consists of choice of
speed, headway, gap between vehicles at an intersection. In contrast,
operational behaviour consists of steering and handling of the pedals (for
example braking). Rumar et al. (1976) studied the effects of studded tires on
speed choice in curves. Drivers with studded tires drove faster compared to
drivers with unstudded tires in icy road conditions. This did not result in
lower safety, since the ‘safety margin’, defined as the difference between real
and critical lateral acceleration, was larger with studded tires. Summala and
Merisalo (1980) also found that drivers with studded tires chose higher speeds
in curves in low-friction conditions and that the safety margin was greater for
drivers with studded tires in slippery conditions. The higher speeds with
studded tires in low friction conditions may be regarded as an adaptation of
tactical behaviour to the increased friction coefficient induced by studded
tires.</span></span></span></div>
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;">
</span><span style="font-size: 12pt;"></span></span>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;"><span style="font-family: "times new roman" , serif; font-size: 12pt;">Also, the acceleration capability of cars has been shown to affect behaviour.
Evans and Herman (1976) found that drivers accepted smaller gaps with oncoming
cars while negotiating intersections if the acceleration capability of the car
was higher. However, the physical safety margin was not negatively affected by
acceleration capability. Also, newer cars used higher levels of deceleration
compared to older cars when they stopped at signalized intersections (Evans and
Rothery, 1976). This was explained as a possible adaptation of behaviour (on
the tactical level) to compensate for reduced mechanical conditions in older
vehicles.</span></span></span></div>
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;">
</span><span style="font-size: 12pt;"></span></span>
<br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;"><span style="font-family: "times new roman" , serif; font-size: 12pt;">Evans and Wasielewski (1983) found that drivers of newer cars and cars with
intermediate mass followed with a smaller time-headway. This may also be the
result of better deceleration capabilities of newer cars. Evans (1991)
postulated that improved braking and vehicle handling characteristics result in
increased speeds, closer following and higher speeds in curves.</span></span></span></div>
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</span>
</span><br />
<div style="text-align: justify;">
<span style="font-family: "times new roman" , "serif";"><br /></span></div>
<span style="font-family: "times new roman" , "serif";">
<span style="font-size: 12pt;"></span></span>
<div style="text-align: justify;">
<span style="font-family: "times new roman" , "serif";"><span style="font-size: 12pt;"><span style="font-family: "times new roman" , serif; font-size: 12pt;">When safety changes are invisible to the user, as may be the case with seat
belts and increased crashworthiness, there is no evidence of any measurable
human behaviour feedback. A similar point was made by Lund and O’Neill (1986).
Design changes that reduce the likelihood of a crash do have an effect on
behaviour. They stated that how a car is driven depends on feedback to the
driver about the car’s handling characteristics. Vehicle-related factors may
then affect both operational and tactical driver behaviour depending on the
visibility of the feedback. This type of behavioural adaptation has been studied in <a href="http://cs-driving-simulator.com/" target="_blank">a driving simulator</a>.</span></span></span></div>
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DriverSafetyhttp://www.blogger.com/profile/03094173797784413763noreply@blogger.com0