Assessing single motorcycle crash injury severity factor using a novel partial temporally constrained random parameters logit model

Motorcyclists tend to sustain severer injuries in crashes than vehicle occupants. To be able to reduce motorcycle-involved crashes and motorcyclists' injury severities, many previous studies have been conducted to identify injury contributing factors. With the implementation of many countermeasures geared at improving road safety, recent studies have demonstrated temporal variations in crash-contributing factors — implying that countermeasure implementation should not be static over a long period. However, previous studies were not able to easily determine the temporal variations associated with the individual crash-contributing factors. This study adopts the novel partial constraint modelling technique to track the temporal instability of crash factors associated with motorcyclists' injury severity in single-vehicle motorcycle crashes. Using real-time weather information and other influential factors, variables that significantly contribute to motorcyclist injury severity were identified. Weather variables like wind speed, air temperature and visibility were found to significantly affect single motorcycle crash severity.