Hazard anticipation of young novice drivers - SWOV

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selection task cannot be used to test hypothesis 3 of Section 4.1.8 that the emotional and motivational aspects of hazard anticipation improve with age. 4.3.4. Relationship between tasks and visual perception On average the norm score on the MVPT-3 was M = 106.9 (SE = 3.3) for young novice drivers, M = 110.3 (SE = 3.6) for older novice drivers and M = 112.0 (SE = 2.8) for experienced rivers. The average norm score in the population per age group is 100. The differences between the groups were not significant, F(2,68) = 0.73, p = .49. Table 4.4 shows the overall correlation and the correlations per group between the norm scores on the MVPT-3 and the mentioned latent hazards on the hazard detection and recognition task. Table 4.4. Correlation between norm scores on the MVP-3 and the mentioned latent hazards on the hazard detection and recognition task. GROUP Pearson's correlation coefficient r between norm scores MVPT-3 and mentioned latent hazards p Overall .35
and risk assessment). The principal hypothesis was that the cognitive aspect mainly improves with experience and that the emotional and motivational aspect mainly improves with age (i.e. maturation of predominantly the PFC). In order to test this hypothesis, two hazard anticipation tasks were developed: a hazard detection and recognition task presumed to measure in particularly the cognitive aspect of hazard anticipation and a risk assessment and action selection task presumed to measure in particularly the emotional and motivational aspect of hazard anticipation. Three groups made the two tasks: young learner drivers that started to take driving lessons as soon as the age limit was reached; older learner drivers that started to take driving lessons when they were 25 years of age or older; and experienced drivers. Young learner drivers and older learner drivers showed significantly less anticipatory eye glances in situations with covert latent hazards than experienced drivers and there was no significant difference between young learner drivers and older learner drivers. This result is in support of the hypothesis that the cognitive aspect of hazard anticipation improves with experience as far as covert latent hazards concerned. Indications that novice drivers have problems detecting and recognizing covert latent hazards in studies using video clips and eye tracker equipment, were found before (Borowsky et al., 2010; Underwood, Chapman, et al., 2002). However, as in these studies no comparison was made between novice drivers that start to drive late in life and novice drivers that start to drive early in life, these studies did not provide indications whether poor detection and recognition of covert latent hazards is mainly a matter of lack of experience or mainly a matter of age. Pradhan et al. (2005) also found that novice drivers made fewer anticipatory eye glances than experienced drivers in situations with latent hazards of which most of the latent hazards were covert latent hazards. However, in this study participants drove in a simulator. It could be argued that novice drivers make less anticipatory eye glances while driving because the execution of the driving task (manoeuvring, shifting gear, the mastering of basic traffic situations) is not yet performed at the procedural stage (Anderson, 1982). Because of this, more mental capacity is needed for driving itself and therefore less mental capacity can be allocated to the anticipation of possible hazards. Underwood, Chapman et al. (2002) found that novice drivers did not adapt their visual scanning patterns as well as experienced drivers did to the type of road (rural roads versus urban roads) even when they watched videos and did not have to drive. In the study presented in this chapter, learner drivers made less anticipatory eye glances than experienced drivers while they did not have to drive. Both the study of 166
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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
Page 116 and 117: 4. Hazard anticipation, age and exp
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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 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
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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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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