Hazard anticipation of young novice drivers - SWOV

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Discussion about fixated latent hazards and mentioned latent hazards Fixations on overt latent hazards can be the result of different mechanisms. Firstly as was noted before, in situations with overt latent hazards a fixation on another road user is possible without having any expectations that this other road user may start to act dangerously. Secondly, a fixation can be the result of a bottom-up process, but after having 'seen' that other road user more or less accidentally, a driver may realize that this other road may start acting dangerously in the given circumstances. This is to say that a bottomup fixation or a top-down fixation not related to hazard perception has led to the activation of the proper schema for noticing the overt latent hazard. Thirdly, a fixation on another road user can be purely the result of a topdown process related to hazard anticipation. A saccade then is made in the direction of the other road user with the intention to fixate (keep an eye on) this other road user because, based the activated dominant schema, it is expected that in situations like this, particular road users may show dangerous behaviour. These top-down fixations can be automatic when it is a routine overt latent hazard and can be controlled when it is a discovered new type of overt latent hazard. In the first situation, participants will not mention the overt latent hazard because for them there was no overt latent hazard. In the second and third situation, participants may mention the hazard only when this overt hazard was a serious possible threat for them. In none of the video clips the latent hazards developed into an imminent hazard that required immediate action to avert a crash. When the risk assessment by the participants was low and the overt latent hazard did not materialize, it is likely that the overt latent hazard was immediately forgotten and therefore not mentioned, especially when the latent hazards were 'routine hazards' that did not require involvement of the SAS (see Section 3.8 and Section 4.1.6). This could explain why the percentages mentioned overt latent hazards were also lower than the percentages fixated overt latent hazards for the group of experienced drivers. In contrast to fixations on overt latent hazards, fixations on covert latent hazards are very likely only top-down and related to hazard anticipation, as there has to be a reason why drivers look in directions where at the particular nothing special can be seen. One can argue that fixated covert hazards that are not mentioned, are more often automated top-down fixations. If this is the case, fixations are made based on the dominant schema that was selected within the CS, without involvement of the SAS (the gray arrow from 'Competitive selection' to 'Gaze control' in Figure 4.1). As these 157
more or less automatic fixations require no decisions based on the processing of information in working memory, they are presumably easily forgotten when the latent hazard does not manifest itself. One can also argue that topdown fixations on covert hazards are mostly not made automatically and require involvement of the SAS. When this is the case, fixated covert latent may be forgotten and not mentioned because the covert latent hazard did not materialize and the risk was assessed as relatively low. If the former hypothesis would be true, the discrepancy between fixated covert latent hazards and mentioned covert latent hazards has to be larger for experienced drivers than for both young learner drivers and older learner drivers, as experienced drivers are supposed to have more automated gaze control. This hypothesis is not supported as the difference between fixated covert hazards and mentioned covert hazards was about the same for learner drivers and for experienced drivers, t (38.8) = 0.28, p = .79. If the latter hypothesis would be true, the discrepancy between fixated covert latent hazards and mentioned covert latent hazards has to be larger for young learner drivers than for older learner drivers, as young learner drivers presumably more often underestimate risks and/or overestimate their skills than older learner drivers. This hypothesis is also not supported as the difference between fixated covert hazards and mentioned covert hazards was not significantly larger for young learner drivers than for older learner drivers, t (32) = -1.14, p = .26. It could be that both hypothesised mechanisms were active and that they neutralized each other effect. A scale for the hazard detection and recognition task None of the four variables (fixations on covert latent hazards, fixations on latent hazards, mentioned covert latent hazards and mentioned overt latent hazard) were sufficient internally consistent to be a scale. As it is not exactly clear what the underlying concept of the scales are, scores on the scales cannot be compared with the scores on other tasks (in this case the risk assessment and action selection task) and tests (in this case the visual perception test MVPT-3). When the scores on all the six mentioned covert latent hazards and all the ten overt latent hazards were combined into one variable with the name 'mentioned latent hazard', a variable arose with an acceptable Cronbach's alpha (α = .71). On average young learner driver mentioned 37.7% (SE = 3.1) of the latent hazards. This percentage was 41.4 (SE = 3.5) for older learner drivers and 66.1 (SE = 2.8) for experienced drivers. ANOVA showed that the differences between the groups of mentioned latent hazard were significantly different with a large effect size, F(2,72) = 27.81, p < .001, η 2 P = .44. Post hoc Bonferroni tests showed that on this variable of 158
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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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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 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
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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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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