Hazard anticipation of young novice drivers - SWOV

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mentioned latent hazards, young learner drivers differed significantly from experienced drivers (p < .001) and older learner drivers differed significantly from experienced drivers (p < .001) but young learner drivers did not differ from older learner drivers (p = 1.0). There was a significant relationship between the number of fixated latent hazards and the number of mentioned latent hazard, r = .52, p < .001. The Cronbach's alpha of the combined scores of fixations on latent hazards was not acceptable (α = .62). When in the remainder of this chapter scores on the hazard detection and recognition task are compared with other task and test, only the scores of mentioned latent hazards are considered. Gender The sample size of each group was too small to disaggregate by gender. As in the results presented so far, no significant differences were found between young learner drivers and older learner drivers, these two groups were combined in order to create a sample of learner drivers that was large enough to disaggregate. On average female learner drivers mentioned 36.5% (SE = 3.0) of the latent hazards and male learner drivers mentioned on average 40.4% (SE = 3.4) of the latent hazards. The difference between female learner drivers and male learner drivers was not significant, t (50) = 0.87, p = .39. 4.3.2. The risk assessment and action selection task Risk score For every participant, based on their response ('brake', 'release throttle' and 'do nothing') on each of the twenty-five photographs, one final risk score was calculated. This was done in accordance with the procedure described in Section 4.2.4. The Cronbach's alpha was acceptable (α = .68). Figure 4.10 presents the boxplot of the results. The solid horizontal lines in the boxes indicate the median, the boxes themselves are the interquartile range, and the whiskers indicate the minimum and maximum values. The mean score is not indicated, but is an imaginary horizontal line through the centre of a box. A final score above zero is too risky and a final score lower than zero is too cautious. 159
Figure 4.10. Scores on risk assessment and action selection task per group. The mean scores of young novice drivers, older novice drivers and experienced drivers were respectively; M = 2.61 (SE = 0.76), M = 1.79 (SE = 0.84) and M = 1.00 (SE = 0.65). ANOVA demonstrated that the average scores differed significantly over the three groups with a medium effect size, F(2,71) = 3.63, p < .05, η 2 P = .09. Post hoc Bonferroni tests showed that only young learner drivers differed significantly from experienced drivers (p < .05), but older learner drivers did not differ significantly from experienced drivers (p = .29) and young learner drivers did not differ significantly from older learner drivers (p = 1.0). A t-test for independent samples was conducted, ignoring the existence of the group of experienced drivers. The difference between young novice drivers and older novice drivers was also not significant when this test was conducted, t(40) = 0.69, p = .51. If hypotheses 3 in Section 4.1.8 would be true and the risk assessment and action selection task would really measure the emotional and motivational aspect of hazard anticipation, older learner drivers should have had significantly lower scores on this task than young learner drivers. This is not the case and therefore the results are not in support of hypothesis 3. 160
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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
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
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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 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
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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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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