Abstract
A comprehensive understanding of the relationship between road accident occurrence and severity of consequences permits the formulation of safety measures that are most cost-effective. A disaggregate model of road accident severity based on sequential logit models is presented. The sequential binary approach is able to account for the dependency between different levels of severity. Factors that affect the level of damage experienced by individuals involved in road accidents include the following: accident dynamics, seating position, vehicle condition, vehicle size, driver condition, and driver action. Separate models are calibrated for three accident situations: single-vehicle accidents, two-vehicle accidents, and multi-vehicle accidents. Ontario road accident police reports are used to calibrate and validate the models. The results of a simple application of the models to a safety protocol involving the effectiveness of passenger restraint devices are presented. Key words: road accident severity, personal injury, logit.
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