An Experimental Study into the Impact of Local Accident Information on Driver’s Route Planning Behaviour

Government and regulatory agencies rely on the presentation of national and aggregate statistics to influence driver behaviour. The intention is, for instance, to illustrate the dangers of drink driving by publicising the number of road users who die annually from accidents involving alcohol abuse. These aggregate statistics often have only a limited impact on driver behaviour. Experimental studies have shown the effects of attribution error, it is easy to believe that these adverse events will ‘never happen to me’. The following pages describe the development of a web-based system Geographical Information System that enables drivers to find out about previous accidents on their local roads. Unfortunately, it can be difficult to show that the provision of such information has an impact on driver behaviour. Psychometric risk assessments provide indirect evidence for the utility of such driver information systems. In contrast, this paper goes on to describe an experimental study into the effects that local accident information has on drivers’ route planning tasks. Our results show that information about previous accidents can encourage two cohorts of taxi drivers to change their routes both for areas in which they work and for journeys on roads with which they are less familiar. We chose taxi drivers because these individuals often have the highest exposure to the risks of driving and, consequently, have amongst the highest insurance premiums. The closing sections use the results from this study to inform the development of in-car systems that provide safety-related information based on the frequency of previous accidents just as existing GPS tools provide data about average delays and fuel consumption. Such information will become increasingly important as insurance companies continue to develop GPS-based systems derived from Electronic Road Pricing applications. These systems will calculate insurance premiums based on risk exposure during individual journeys rather than charging drivers an annual aggregate fee.