Hazard anticipation of young novice drivers - SWOV

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difference between overt latent hazards and covert latent hazards. The experts were instructed to take pictures of road and traffic situations with no hazards; with latent hazards (both covert latent hazards and overt latent hazards); and with imminent hazards. In combination with the depicted speeds, the correct response of the photographs with no hazards was considered to be 'do nothing', of photographs with latent hazards 'release throttle' and of photographs with imminent hazards 'brake'. In order to verify these responses, fifteen experts, not involved in the production of the photographs, were asked to do the task with fifty photographs. These experts were partly employees of CBR and partly experts from other organisations (e.g. driving instructors). Pictures were only included in the task if 80% of the experts provided the same response. Of the twenty-five photographs in the task, in nine items the correct response was 'brake', also in nine items the correct response was 'release throttle' and in seven items the correct response was 'do nothing'. An example of each category is presented in Appendix 2. The full set could not be reproduced, as the photographs are also used in the theory test of the Dutch driving test. Visual perception test The skill to detect a latent hazard in a visually complex environment could be related to the someone's visual perception abilities in general. With visual perception is not meant someone's visual acuity, but the ability to understand what is seen in a visually complex environment. It could be that persons do not recognize hazards in a visually complex environment not so much because they have no knowledge about the type hazard, but because they cannot detect it due to the visual complexity of the situation. In order to test if there is a correlation between the two previously described hazard anticipation tasks and visual perception, all participants performed a validated visual perception test. This test was the third edition of the Motorfree Visual Perception Test (MVPT-3) (Colarusso & Hammill, 2003). In combination with other tests the MVTP is used to assess fitness to drive in older drivers (i.e. drivers of sixty-five years of age and older). A significant correlation was found between on-road driving tests and MVPT scores (Mazer, Korner-Bitensky, & Sofer, 1998). Although MVPT-3 is composed of different sub-tests (spatial relationship, visual discrimination, figure-ground, visual closure and visual memory), one score is calculated. It took about 30 min to complete the test. 141
Questionnaire All participants had to complete a short questionnaire with questions about demographics, their driving experience and the quality of their eyesight. For the learner drivers (both young and old), experience meant the number of hours behind the wheel when driving with a driving instructor. In contrast with many other countries, accompanied driving with for instance a parent in the learner phase (i.e. before having passed the driving test) was not possible in the Netherlands at the time the experiment was conducted. For the experienced drivers, experience meant the number of years in possession of the driving licence (more than 10) and the annual mileage in the past year (at least 15,000 km). Eye tracking The video clips and the photographs were displayed on a 17'' monitor (aspect ratio 4:3) with an integrated non-intrusive eye tracker and a data rate of 120 Hz. This eye tracker was a Tobii T120. The resolution was set on 1024 × 768 and both the video clips and the photos were presented full screen. The average distance from the eyes of the participants to the middle of the screen was approximately 60 cm, which provided them with a horizontal visual field of about 32°. See Figure 4.5 for an impression. Figure 4.5. Test setup with eye tracker. 142
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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
Page 91 and 92: elatively high speed in the same di
Page 93 and 94: only associated with top-down activ
Page 95 and 96: information transformation processe
Page 97 and 98: (consciously) controlled action reg
Page 99 and 100: on the left lane of a motorway (in
Page 101 and 102: 3.7.1, 3.7.2 and 3.7.3. This is don
Page 103 and 104: driver does not think that she or h
Page 105 and 106: for experienced drivers even in cir
Page 107 and 108: sound was heard) and some participa
Page 109 and 110: stage. In this stage, learners comm
Page 111 and 112: A theory that explains how we may l
Page 113 and 114: were about to turn left while their
Page 116 and 117: 4. Hazard anticipation, age and exp
Page 118 and 119: 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 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 170 and 171: more difficulties to detect and rec
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
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The mean click score was M = 7.7 (S
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ottom-up gaze control (the tractor
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6. Simulator-based hazard anticipat
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al., 2002; Regan, Triggs, & Godley,
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esources to vehicle control (steeri
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of the University of Massachusetts
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In contrast, Ivancic & Hesketh (200
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students, whereas participants that
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for the training were based on thos
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6.2.3. Training intervention SimRAP
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A screen capture of the centre scre
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Table 6.2. (continued) critical sit
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at least sixteen of the nineteen si
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latent hazards. This is not very su
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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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