Hazard anticipation of young novice drivers - SWOV

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animation clips were made, each lasting about thirty-five seconds. All videos were 'taken' from the driver's perspective. Animation was used because it is easier to stage scenes in animation videos than in real life videos. In none of the clips the hazards materialized. This means that no car suddenly emerged from behind an object that blocked the view and no other road users performed risky actions. An interactive pointing system (with a computer mouse) was applied. At certain moments in each clip, the clip was paused for 5 s. These short pauses with a frozen traffic situation on the screen were necessary to allow participants to make mouse clicks. During these pauses participants could click on covert latent hazards and on overt latent hazards. They also could click on small rectangles located at the left and right side of the screen. With a mouse click on the right rectangle participants could indicate that they would have looked to the right in search of a hazard if this would have been possible. With a mouse click on the left rectangle participants could indicate the same for hazards to the left. In each pause only the first three clicks, including the clicks on the rectangles were recorded. To ensure that participants concentrated on the task and did not randomly click as many times as possible, participants were told that clicks on irrelevant spots would lower their score. Not all pauses contained three latent hazards and in some pauses, there were no latent hazards at all. A disadvantage of pauses is that participants can reorient themselves (McGowan & Banbury, 2004). This is to say, the very fact that a video clip pauses, could be a cue for participants to start searching for latent hazards they had not noticed while the video was still running. The pause itself, in contrast to driving in the real world, also facilitates participants with time to search for these possible latent hazards. This was another reason to instruct participants in advance that false clicks would lower their score and to keep the pauses short (5 s). Just as in the hazard detection and recognition task of Chapter 4, before the start of each video clip a plan view was presented of the manoeuvre the car would make in the video clip. The number of pauses per video clip differed and ranged between three and six per clip. When a pause started, a countdown timer was visible on the bottom of the screen, indicating the time left for pointing and clicking. On spots where a click was made a green cross appeared. However, after three clicks in a pause no more crosses appeared when a click was made. In contrast to video clips used in Chapter 4, no part of a dashboard and a steering wheel was visible. See for an example of a pause Figure 5.3. 175
Figure 5.3. Screen capture of a pause in the video task. In this video, the driver turns left. A click on a rectangle to the left or to the right meant that participants wanted to look either left or right in this situation if possible. The dark bar underneath the picture is the countdown timer. The coordinates of the clicks were automatically captured in a database. For scoring, so called 'hot spots' were defined. A click within the area of a hot spot resulted in a score. Clicks in the hot spots that contained the covert latent hazard and/or the overt latent hazards were rewarded with four points. Clicks in hot spots that provide relevant information about the developing situation (e.g. a traffic sign that tells the driver that she or he is approaching a dangerous intersection) were scored with one point. Clicks in hot spots that were completely irrelevant (e.g. a sign with no relevant information for the driver) were scored -1. The hotspots were defined in close cooperation with three experienced driving examiners. Subsequently, the complete test and the scoring system were reviewed by six driving examiners who were not involved the development of the video task. Based on their remarks, hotspots were revised. 176
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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
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overview of their studies: McKenna
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with regard to the risk felt in the
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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 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 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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Page 220 and 221: For the control group the opposite
Page 222 and 223: The combined three near transfer si
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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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