Hazard anticipation of young novice drivers - SWOV
Hazard anticipation of young novice drivers - SWOV
Hazard anticipation of young novice drivers - SWOV
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hazards are a good indicator <strong>of</strong> someone’s ability to detect and recognize<br />
covert latent hazards.<br />
The study presented in Chapter 5 was on practical methods to measure<br />
various aspects <strong>of</strong> hazard <strong>anticipation</strong> that are suitable for mass testing. The<br />
results show that on the developed photo task, learner <strong>drivers</strong> (tested on the<br />
day they had passed the driving test) responded riskier with regard to speed<br />
adaptation than both <strong>novice</strong> <strong>drivers</strong> with 18 months driving experience and<br />
experienced <strong>drivers</strong> did. In addition, <strong>novice</strong> <strong>drivers</strong> who had reported a<br />
crash had riskier responses than crash free <strong>novice</strong> <strong>drivers</strong>. These are<br />
indications that the photo task has validity. On the developed video task<br />
with pauses in which participants could click on latent hazards however,<br />
only a marginally significant difference between crash free <strong>novice</strong> <strong>drivers</strong><br />
and <strong>novice</strong> <strong>drivers</strong> that had reported a crash was found. Moreover, on this<br />
video task, no significant difference was found in detected and recognized<br />
latent hazards between learner <strong>drivers</strong> on the day they passed the driving<br />
test and pr<strong>of</strong>essional <strong>drivers</strong>. The conclusion is that in principle the photo<br />
task is a good method to test hazard perception and the video task with<br />
mouse clicks on latent hazards during pauses in the clips, is not. The results<br />
<strong>of</strong> Chapter 4 however indicate, that a video task (but not with pauses and<br />
mouse clicks) has more potential to discriminate between good and bad<br />
<strong>drivers</strong> in hazard <strong>anticipation</strong> than the photo task.<br />
The results the study presented in Chapter 6 show that it is possible to<br />
train visual search for latent hazards in a training program <strong>of</strong> approximately<br />
one hour on a simple simulator. According to Elvik (2010), the <strong>young</strong> <strong>novice</strong><br />
driver problem is almost impossible to solve as "the high risk <strong>of</strong> <strong>young</strong><br />
<strong>drivers</strong> is probably attributable to a powerful mixture <strong>of</strong> biological factors<br />
(hormones and brain development), overoptimistic self-assessments and<br />
being in a phase <strong>of</strong> life in which becoming independent, testing limits and<br />
rebelling against adult values is important." This all may be true but there is<br />
hope. Lack <strong>of</strong> hazard <strong>anticipation</strong> skills is one <strong>of</strong> the causes why <strong>novice</strong><br />
<strong>drivers</strong> have such a high crash rate (Congdon, 1999; Curry et al., 2011;<br />
McKenna & Horswill, 1999; McKnight & McKnight, 2003; Wells et al., 2008).<br />
The results <strong>of</strong> the studies presented in this thesis indicate that poor hazard<br />
<strong>anticipation</strong> is partly caused by the fact that <strong>novice</strong> <strong>drivers</strong> do not know what<br />
to expect and therefore do not know where to look. The results in this thesis<br />
also indicate that this shortcoming can be overcome by training, without<br />
stimulating the tendency to take more risks, which <strong>of</strong>ten is the case after<br />
completion <strong>of</strong> a short training program in which skills are trained.<br />
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