Sponsoring partner: Nissan
In order to study risk in the driving context, it is necessary to have an operational definition of risk and a method of quantification. Whereas objective risk may not be directly quantified, it may be possible to derive a risk “standard” based on observable context attributes. This standard can be used as a proximal measure of “true” risk to assess the effect of risk information on driver behaviour and the accuracy of subjective risk perception. The LADS was used to study risk perception, in which various metrics of risk were quantified and visually displayed to subject drivers. The risk parameters of severity (kinetic energy) and probability (time headway) were combined in an algorithm to provide a more complete representation of risk that is sensitive to traffic conditions. This “risk” (the result of this algorithm) was presented to the driver via an in-car LCD display mounted on the dashboard. The display was a sliding scale, indicating green for low risk, through to amber and red for high risk. The risk display was evaluated in a simulated urban and rural road environment with scripted, pre-defined events. 30 drivers drove the LADS with a range of driving experience. The display was perceived to be credible and useful and it showed consistent safety trends and significant safety benefits for certain events.