Hazard anticipation of young novice drivers - SWOV

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framework of Brouwer & Schmidt (2002) was applied. The key concept in this framework is mental representation or schema. While driving, schemata unfold in interaction with external stimuli (i.e. what the driver perceives) and internal stimuli (i.e. what the driver feels). The selected overarching dominant schema at any point in time, enable the driver to find relevant information in the road and traffic situation and to anticipate forthcoming events. Activation and inhibition of schemata and action selection most of the times happen automatically, especially when the driver is an experienced driver. Sometimes selection of schemata is controlled. The framework describes the hypothetical sub-processes that are involved in action selection by drivers and the interaction between these sub-processes. The framework of Brouwer & Schmidt (2002) is based on Norman & Shallice's model on willed and automatic control of behaviour (1986) and incorporates some elements of the zero-risk model on driver behaviour developed by Näätänen & Summala (1974). In contrast to Norman & Shallice, Brouwer & Schmidt make way for emotional and motivational processes in their framework and attention is not only manifest in controlled hazard anticipation but also in automatic hazard anticipation. Brouwer & Schmidt (2002) also assume that action selection in complex cognitive tasks always is a mixture of automatic and controlled processing. It is hypothesised that 'somatic markers' (Damasio, 1994) help to select the proper dominant schema. Somatic markers are little emotional signals from the viscera that have been developed from emotions felt in previous situations in which a similar latent hazard has materialized. These somatic markers may help to speed-up schema selection and decision-making. It is assumed that the schemata of young novice drivers are less elaborated and that they do not have all the somatic markers that are necessary to recognize latent hazards and to respond swiftly once a latent hazard is recognized. With regard to the cognitive aspect and the emotional and motivational aspect of hazard anticipation, it was hypothesised that the cognitive aspect mainly improves with experience and the emotional aspect mainly improves with age (maturation of the brain). In order to test this, two tasks were developed: a hazard detection and recognition task and a risk assessment and action selection task. Chapter 4 describes the development of the two tasks, the method how the hypothesis was tested and the results of the tests. The hazard detection and recognition task consisted of seven animated video clips, 'taken' from the driver's perspective and each lasting approximately forty seconds. These video clips contained overt latent hazards and covert latent hazards that did not materialize. While participants watched these 265
videos, their gaze directions and fixations were recorded. Immediately after each video, participants were asked what could have happened (that did not happen) that would have increased the likelihood of a crash. It was assumed that this task primarily tested the ability to detect and recognize latent hazards. The risk assessment and action selection task consisted of twentyfive photographs. Each photograph was exposed for eight seconds on the screen of a monitor. These photographs were taken from a driver's perspective. A part of the photographs contained imminent hazards (i.e. visible other road users that would collide with the driver (of the photograph) if no one would change speed and/or course). A part of the photographs contained latent hazards (both covert latent hazards and overt latent hazards) and a part of the photographs contained no hazards at all. After participants had watched a photograph (during eight seconds) and the screen had turned black, participants had to respond if they would have (1) braked in this situation (in case of an imminent hazard), (2) released the throttle in this situation (in case of a latent hazard), or (3) would have continued with the same speed (in case of no imminent or latent hazard). While participants watched the photographs on a monitor, their gaze directions and fixations were recorded. It was assumed that the responses on this task would primarily indicate the inclination to take risks as research with similar sets of photographs had shown that there is no difference between novice drivers and experienced drivers in the ability to categorize photographs with imminent hazards, latent hazards and no hazards (Huestegge et al., 2010; Kelly et al., 2010). Participants in three different groups did both tasks. This was a group of young learner drivers (18 or 19 years of age) that were almost ready to do the driving test, a group of older learner drivers (25 years of age or older) that also were almost ready to do the driving test and a group of experienced drivers. On the hazard detection and recognition task, experienced drivers fixated covert latent hazards significantly more often than young learner drivers did and older learner drivers did. There was no significant difference in fixated covert latent hazards between young learner drivers and older learner drivers. Exactly the same pattern was visible in the mentioned covert latent hazards. However in all three groups, on average around 30% less covert latent hazards were mentioned than fixated. Almost all the participants in all three groups fixated all the overt latent hazards and there was no significant difference between the groups in fixated overt latent hazards. In contrast, experienced drivers mentioned significantly more often overt latent hazards than both young learner drivers did and older learner drivers did. There was no significant difference in mentioned overt latent hazards between young learner drivers 266
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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
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of the visual acuity in the fovea.
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working memory. Both bottom-up proc
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without gaze control (the gray arro
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urban areas than on rural roads, no
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the right between the parked cars i
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that in the video clips no visible
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• Young learner drivers (age rang
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• Did you have moments that you t
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difference between overt latent haz
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4.2.3. Procedure On arrival, the ex
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ecognition task, risk assessment an
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Table 4.1. Percentage of the partic
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that cognitive aspects of hazard an
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80 70 Mean percentage mentioned cov
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Table 4.3. Percentages of latent ha
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latent hazards was higher than the
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Discussion about fixated latent haz
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mentioned latent hazards, young lea
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Gaze directions and fixation durati
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4.3.3. Relationship between the two
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selection task cannot be used to te
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Underwood, Chapman et al. (2002) an
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more difficulties to detect and rec
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5. Testing hazard anticipation, an
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• The video task and the photo ta
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animation clips were made, each las
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The photo task Three experts on the
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5.2.3. Procedure Participants were
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5.2.6. Overt and covert latent haza
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The effect size was small, η 2 P =
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action selection task of Chapter 4,
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3. Effect of interruptions The inte
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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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Page 220 and 221: For the control group the opposite
Page 222 and 223: The combined three near transfer si
Page 224 and 225: training program was mostly on over
Page 226 and 227: 7. Discussion and conclusions 7.1.
Page 228 and 229: ehaviour could be the cause of unsa
Page 230 and 231: transport. It can also be status, a
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Page 234 and 235: performance in hazard detection and
Page 236 and 237: than both other groups. It is likel
Page 238 and 239: etter scanning for latent hazards i
Page 240 and 241: hazards are a good indicator of som
Page 242 and 243: order to avoid attribution of an ex
Page 244 and 245: References Abelson, R.P. (1981). Ps
Page 246 and 247: underlying reaction time to visual
Page 248 and 249: Darby, P., Murray, W. & Raeside, R.
Page 250 and 251: Fuller, R. (2007b). Motivational de
Page 252 and 253: Irwin, D.E. (2004). Fixation locati
Page 254 and 255: Louwerens, J.W., Gloerich, A.B.M.,
Page 256 and 257: Murray, Å. (1998). The home and sc
Page 258 and 259: Roth, M. (2009). Social support as
Page 260 and 261: Ulleberg, P. (2001). Personality su
Page 262 and 263: Summary Driving most of the times,
Page 264 and 265: Deficit Hyperactivity Disorder (ADH
Page 268 and 269: and older learner drivers. From the
Page 270 and 271: prepare participants for the tasks.
Page 272: group than before the training and
Page 275 and 276: verkeer. Het probleem van de jonge
Page 277 and 278: status en een auto betekent ook vri
Page 279 and 280: Belangrijk is dat zowel bij zichtba
Page 281 and 282: en ervaren bestuurders (Huestegge e
Page 283 and 284: afgerond, hadden ook een significan
Page 285 and 286: om hun veiligheidsmarge te vergrote
Page 288: About the author Willem Vlakveld wa
Page 291 and 292: 4. On a rural road when driving str
Page 293 and 294: they keep on walking in the same di
Page 295 and 296: 5. The driver drivers straight on a
Page 298 and 299: Appendix 3 Additional latent hazard
Page 300 and 301: Appendix 4 Glossary of abbreviation
Page 302 and 303: economic progress and world trade.
Page 304 and 305: Appendix 5 Glossary on brain issues
Page 306 and 307: Gonadotropin releasing hormone Gray
Page 308 and 309: MEG Motor cortex MRI Myelination Ne
Page 310 and 311: PFC Serotonin Striatum Synaptic pru
Page 312 and 313: SWOV-Dissertatiereeks In deze reeks
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