Hazard anticipation of young novice drivers - SWOV

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Table 2.1. Relative fatality ratios of young male drivers over the years 2004-2008 of various types of car crashes. Source: Ministry of Infrastructure and Environment / Statistics Netherlands. Crash type in which the driver and or her or his passenger(s) is killed Relative fatality ratio 4 1. single-vehicle 8.5 2. car-car 2.2 3. car-other type of vehicle 1.2 Crash type in which the driver kills persons in other vehicles and or pedestrians 1. car-car 7.4 2. car-other type of vehicle 4.1 Table 2.1 indicates that controlled for exposure it was 8.5 more likely that the young driver in a fatal single-vehicle crash was a young male driver (aged 18-24) than a young female driver (aged 18-24). And controlled for exposure it was 7.4 more likely that the young driver (aged 18-24) was male that collided with another car in which at least one other person was killed. These differences are quite dramatic and cast serious doubts on the fitness to drive of young males. This is of course a major impetus for the research carried out in this thesis. An in-depth analysis of fatal crashes in which young male and female drivers (aged 18-21) were the culpable party was conducted in Finland (Laapotti & Keskinen, 1998). Of the 413 fatal crashes included in that study, 338 times a young man was the driver and 75 times a young woman was the driver. The percentage 'loss-of-control' crashes was about the same for young male and young female drivers (65.7% and 64.0% respectively). When a driver loses control the driver can run of the road (and hit a tree) (a single-vehicle crash), but the driver can also hit another car or another type of vehicle or a pedestrian (car-car crash or car-other vehicle type crash). For young male drivers, most of the times a loss-of-control crash was a single-vehicle crash (in about 75% of the cases) and for young female drivers a loss of control crash was most of the times a car-car or a car-other vehicle type crash (in about 65% of the cases). Typically, young male drivers' loss of control crashes 4 Fatalities per distance driven of young male drivers divided by fatalities per distance driven of young female drivers 33
took place in the evening and at night. The speed was often much too high (in 83% of the cases) and in about half of the cases the young male driver was under the influence of alcohol. The loss-of-control crashes involving young female drivers most of the times occurred in daylight. In 40% of the cases, the young female driver drove too fast and in 6% of the cases, the young female driver was under the influence of alcohol. Young female drivers had significantly more loss-of-control crashes on slippery roads than young male drivers. The results suggest that for young male drivers, loss-of-control is more often the result of risk taking behaviour (speeding, driving while under the influence of alcohol) and for young female drivers more often the result of poor vehicle handling. Structural brain differences Could the differences in crash rates and types of crashes between young female drivers and young male drivers be caused by differential developments of their brains? Differences in behaviour between young females and young males may be caused by cultural differences (the way boys and girls are educated and socialized), by biological differences and of course by a combination of the two. In this section, the biological differences will be discussed and in the section about lifestyle (Section 2.4.1) the cultural differences will be discussed. There are some quantitative differences between the average adult brain of females and the average adult brain of males, but there is also considerable variance within each sex and consequently there is a substantial overlap between brains of men and women. Overall, the total cerebral volume is on average about 10% less in adult females than in adult males. Adult females have less gray matter and less white matter than adult males, even after accounting for sex differences in overall body height and weight. When however expressed as a percentage of total brain volume, sex differences in the volume of white matter disappear. Whether this is also the case for gray matter is inconclusive (Paus, 2009). Only a few regions are on average larger in the male brain than in the female brain, including the amygdala and the hippocampus. There are however also a few regions that are on average lager in the adult female brain than in the adult male brain, including the OFC, the anterior cingulate gyrus, the posterior cingulate gyrus (has a memory related function and gets activated by emotional stimuli), the inferior frontal gyrus (plays a role in inhibition and risk aversion) and the corpus callosum (the connection between the right and left cerebral hemispheres) (Paus, 2009). 34
Page 1 and 2: Hazard anticipation of young novice
Page 3 and 4: SWOV-Dissertatiereeks, Leidschendam
Page 5 and 6: Promotores: Prof. dr. W.H. Brouwer
Page 7 and 8: development of hazard perception te
Page 10 and 11: Table of contents 1. General introd
Page 14 and 15: 1. General introduction 1.1. Hazard
Page 16 and 17: 27% of all driver fatalities were d
Page 18 and 19: eported 73 car crashes during the p
Page 20 and 21: with respondents that started their
Page 22 and 23: 2. Determinants that influence haza
Page 24 and 25: planning of a trip, choice of the m
Page 26 and 27: that encompasses the entire second
Page 28 and 29: peaks at 16.7 years of age in girls
Page 30 and 31: Figure 2.2. Model of the different
Page 32 and 33: Keating (2007) mentioned the matura
Page 36 and 37: When do these sex differences emerg
Page 38 and 39: Functional brain differences in boy
Page 40 and 41: oth groups had in common was their
Page 42 and 43: 3. Extroversion: Extrovert persons
Page 44 and 45: is less in these brain areas, but a
Page 46 and 47: 2.4.2. Peer group influences In ado
Page 48 and 49: deduced that car drivers younger th
Page 50 and 51: or little interference with the dri
Page 52 and 53: 2.4.4. Socioeconomic and cultural b
Page 54 and 55: Preusser, 2002). The crash rate of
Page 56 and 57: impact on road safety. Despite the
Page 58 and 59: condition for the older, more exper
Page 60 and 61: person (e.g. a passenger or a pedes
Page 62 and 63: tasks was 3.10, 95% CI [1.73, 5.47]
Page 64 and 65: traffic situation is safe enough to
Page 66 and 67: 2.6.1. Exposure In Section 1.2, the
Page 68 and 69: 58 56 Male Drivers Female Drivers S
Page 70 and 71: 100 Killed car occupants aged 18-24
Page 72: less well equipped to detect and re
Page 75 and 76: 3.2. Hazard anticipation A hazard i
Page 77 and 78: Drivers are aware of hazards when t
Page 79 and 80: 1. Possible other road users on col
Page 81 and 82: oriented and the vertical axis is t
Page 83 and 84: away from me, given the particular
Page 85 and 86:
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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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
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
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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
Page 293 and 294:
they keep on walking in the same di
Page 295 and 296:
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
Page 308 and 309:
MEG Motor cortex MRI Myelination Ne
Page 310 and 311:
PFC Serotonin Striatum Synaptic pru
Page 312 and 313:
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