Development of a safety performance function for motorcycle accident fatalities on Malaysian primary roads

Abstract

This study uses a generalized linear model approach, i.e. negative binomial regression, to develop a predictive model for motorcycle fatal accidents on Malaysian primary roads. For the modeling process, a huge data inventory has been carried out, integrating the road geometry features, fatal accident records and traffic censuses from 3 selected states for the past 3-year period. The results show that motorcycle fatalities per kilometer on primary roads are statistically significantly affected by the average daily number of motorcycles and the number of access points per kilometer. The model established for this study can also be regarded as the first motorcycle safety performance function in Malaysia and probably in Asia. Also noted in this study is the need to establish a proper and systematic road geometry and traffic census inventory in order to develop better accident prediction models for Malaysia in the future.