Hazard anticipation of young novice drivers - SWOV

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more difficulties to detect and recognize covert latent hazards than to detect and recognize overt latent hazards. The detection and recognition of a covert latent hazard requires the selection of a dominant schema that can predict the hazard on context aspects only. The possibility of an invisible other road user on collision course is something the driver has to infer from other visual cues (e.g. 'there can be something behind this lorry that blocks my view'). On the other hand, in case of overt latent hazards content aspects are visible. To put it differently: It is probably more difficult to expect things to happen without direct visible cues than to expect actions from others who are visible. As fixations on overt latent hazards not necessarily indicate that an overt latent hazard was recognized, only differences in mentioned overt latent and covert latent hazards in each group can provide information in support or not in support of the hypothesis. For both young learner drivers and older learner drivers the percentage of mentioned covert latent hazards was significantly lower than the percentage of mentioned overt latent hazards, but the difference in percentages mentioned overt latent hazards and mentioned covert latent hazards was not significant for experienced drivers. These results are in support of the hypothesis. Interestingly, the hazard detection and recognition task could be developed into a diagnostic tool for (learner) drivers to test their cognitive aspect of hazard anticipation, without the use of an eye tracker. The scale of mentioned latent hazards (overt and covert latent hazards combined) had an acceptable internal reliability, there was a large difference between experienced drivers and inexperienced driver and the relationship between fixated covert latent hazards and mention covert latent hazards was substantial. Jackson et al. (2009) used a slightly different task. In this task video clips were paused when overt latent hazards just became visible, but had not (yet) developed into an imminent threat. The screen turned black and participants had to tell what could happen next. Jackson et al. (2009) also found that experienced drivers mentioned significantly more potential hazards than inexperienced drivers. In the present study, participants watched short video clips in which overt latent hazards and covert latent hazards did not materialize. Directly after each clip participants were asked what could have happened that did not happen. Participants could also mention what drew their attention while they watched the video clip. An advantage of the method used in the present study is that participants are not triggered by what they have seen immediately before the video clip stopped. It could be that when the video stops after the first signs of the development of an overt latent hazard, this hazard was not recognized just 169
efore the video halted and the screen turned black. The very fact that the video stopped at that particular moment may help the participant realize that there could have been a hazard (McGowan & Banbury, 2004), even when the screen has turned black. A disadvantage of asking participants what could have happened that did not happen at the end of a video clip, the method applied in the present study, is that participants may have forgotten the latent hazard, even when a video clip lasts no longer than 40 s. A limitation of the study presented in this chapter is that the samples of young novice drivers and older novice drivers may be biased. Age may be not the only difference between the two groups. It is practically impossible to assign participants randomly to a group by telling one participant you do the driving test now and to the other participant you do the driving test over seven years. There may be motives for the choice to start driving early in life or to start driving late in live that affect hazard anticipation. 170
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Hazard anticipation of young novice
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SWOV-Dissertatiereeks, Leidschendam
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Promotores: Prof. dr. W.H. Brouwer
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development of hazard perception te
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Table of contents 1. General introd
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1. General introduction 1.1. Hazard
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27% of all driver fatalities were d
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eported 73 car crashes during the p
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with respondents that started their
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2. Determinants that influence haza
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planning of a trip, choice of the m
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that encompasses the entire second
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peaks at 16.7 years of age in girls
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Figure 2.2. Model of the different
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Keating (2007) mentioned the matura
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Table 2.1. Relative fatality ratios
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When do these sex differences emerg
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Functional brain differences in boy
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oth groups had in common was their
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3. Extroversion: Extrovert persons
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is less in these brain areas, but a
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2.4.2. Peer group influences In ado
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deduced that car drivers younger th
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or little interference with the dri
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2.4.4. Socioeconomic and cultural b
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Preusser, 2002). The crash rate of
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impact on road safety. Despite the
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condition for the older, more exper
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person (e.g. a passenger or a pedes
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tasks was 3.10, 95% CI [1.73, 5.47]
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traffic situation is safe enough to
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2.6.1. Exposure In Section 1.2, the
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58 56 Male Drivers Female Drivers S
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100 Killed car occupants aged 18-24
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less well equipped to detect and re
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3.2. Hazard anticipation A hazard i
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Drivers are aware of hazards when t
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1. Possible other road users on col
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oriented and the vertical axis is t
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away from me, given the particular
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the task demands. The range of acce
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Figure 3.4. Zero-risk model (Näät
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with FTD, poor monitoring of the ri
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elatively high speed in the same di
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only associated with top-down activ
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information transformation processe
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(consciously) controlled action reg
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on the left lane of a motorway (in
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3.7.1, 3.7.2 and 3.7.3. This is don
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driver does not think that she or h
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for experienced drivers even in cir
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sound was heard) and some participa
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stage. In this stage, learners comm
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A theory that explains how we may l
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were about to turn left while their
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4. Hazard anticipation, age and exp
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hazards, drivers have to imagine a
Page 120 and 121: overview of their studies: McKenna
Page 122 and 123: with regard to the risk felt in the
Page 124 and 125: Participants were requested to pres
Page 126 and 127: of the visual acuity in the fovea.
Page 128 and 129: working memory. Both bottom-up proc
Page 130 and 131: without gaze control (the gray arro
Page 132 and 133: urban areas than on rural roads, no
Page 134 and 135: the right between the parked cars i
Page 136 and 137: that in the video clips no visible
Page 138 and 139: • Young learner drivers (age rang
Page 140 and 141: • Did you have moments that you t
Page 142 and 143: difference between overt latent haz
Page 144 and 145: 4.2.3. Procedure On arrival, the ex
Page 146 and 147: ecognition task, risk assessment an
Page 148 and 149: Table 4.1. Percentage of the partic
Page 150 and 151: that cognitive aspects of hazard an
Page 152 and 153: 80 70 Mean percentage mentioned cov
Page 154 and 155: Table 4.3. Percentages of latent ha
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Page 158 and 159: Discussion about fixated latent haz
Page 160 and 161: mentioned latent hazards, young lea
Page 162 and 163: Gaze directions and fixation durati
Page 164 and 165: 4.3.3. Relationship between the two
Page 166 and 167: selection task cannot be used to te
Page 168 and 169: Underwood, Chapman et al. (2002) an
Page 172 and 173: 5. Testing hazard anticipation, an
Page 174 and 175: • The video task and the photo ta
Page 176 and 177: animation clips were made, each las
Page 178 and 179: The photo task Three experts on the
Page 180 and 181: 5.2.3. Procedure Participants were
Page 182 and 183: 5.2.6. Overt and covert latent haza
Page 184 and 185: The effect size was small, η 2 P =
Page 186 and 187: action selection task of Chapter 4,
Page 188 and 189: 3. Effect of interruptions The inte
Page 190 and 191: 5.3.3. Procedure Participants were
Page 192 and 193: The mean click score was M = 7.7 (S
Page 194 and 195: ottom-up gaze control (the tractor
Page 196 and 197: 6. Simulator-based hazard anticipat
Page 198 and 199: al., 2002; Regan, Triggs, & Godley,
Page 200 and 201: esources to vehicle control (steeri
Page 202 and 203: of the University of Massachusetts
Page 204 and 205: In contrast, Ivancic & Hesketh (200
Page 206 and 207: students, whereas participants that
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Page 210 and 211: 6.2.3. Training intervention SimRAP
Page 212 and 213: A screen capture of the centre scre
Page 214 and 215: Table 6.2. (continued) critical sit
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For the control group the opposite
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The combined three near transfer si
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training program was mostly on over
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7. Discussion and conclusions 7.1.
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ehaviour could be the cause of unsa
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transport. It can also be status, a
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of this is an intervention in the a
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performance in hazard detection and
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than both other groups. It is likel
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etter scanning for latent hazards i
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hazards are a good indicator of som
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order to avoid attribution of an ex
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References Abelson, R.P. (1981). Ps
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underlying reaction time to visual
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Darby, P., Murray, W. & Raeside, R.
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Fuller, R. (2007b). Motivational de
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Irwin, D.E. (2004). Fixation locati
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Louwerens, J.W., Gloerich, A.B.M.,
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Murray, Å. (1998). The home and sc
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Roth, M. (2009). Social support as
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Ulleberg, P. (2001). Personality su
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Summary Driving most of the times,
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Deficit Hyperactivity Disorder (ADH
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framework of Brouwer & Schmidt (200
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and older learner drivers. From the
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prepare participants for the tasks.
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group than before the training and
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verkeer. Het probleem van de jonge
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status en een auto betekent ook vri
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Belangrijk is dat zowel bij zichtba
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en ervaren bestuurders (Huestegge e
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afgerond, hadden ook een significan
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om hun veiligheidsmarge te vergrote
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About the author Willem Vlakveld wa
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4. On a rural road when driving str
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they keep on walking in the same di
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5. The driver drivers straight on a
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Appendix 3 Additional latent hazard
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Appendix 4 Glossary of abbreviation
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economic progress and world trade.
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Appendix 5 Glossary on brain issues
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Gonadotropin releasing hormone Gray
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MEG Motor cortex MRI Myelination Ne
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PFC Serotonin Striatum Synaptic pru
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SWOV-Dissertatiereeks In deze reeks
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