Data has been collected from a structured sample of just over 18,500 drivers using a postal questionnaire, to determine the relationship between the accident liability of these drivers and factors such as age, driving experience, sex, socio-economic group and annual mileage. Generalised linear modelling techniques have been used to develop a statistical model which will predict the accident liability - the expected number of accidents per year corrected for memory loss (AC/T) - for an individual driver as a function of relevant explanatory variables. In this context, accidents are all accidents on public roads including damage only accidents. The results indicate that: accident liability is dependent mainly on exposure (total annual mileage), the driver's age and his or her driving experience measured as the number of years since passing the test. The proportion of driving done in the dark and on different types of road (built up, rural, and motorway) also affects accident liability but to a lesser extent. Interactions were also found between age or experience and sex. Predicted accident frequencies are proportional to annual mileage driven. No upturn of accident frequency for older drivers could be detected. Accident involvement falls rapidly after passing the driving test.
Samenvatting