ABSTRACT
This study analyses fatal crash patterns, and identifies the risk factors contributing to motorcycle versus non-motorcycle fatal crashes using binomial logistic regression on two-, four- and six-lane National Highways (NHs) in India utilizing police fatal crash data. The distribution of victims’ mode by striking vehicles shows that percentage share of striking vehicles (truck) against the victims’ vehicles (motorcycle) is 44%, 52% and 37% on two-lane NH-8, four-lane NH-24 and six-lane NH-1, respectively. Nine explanatory variables pertaining to fatal crash, victim, roadway and environment are considered for the model (using combined data of cited three NHs). The results of the logistic regression model (motorcycle versus non-motorcycle fatal crashes) show that for variable ‘collision type’, likelihood of occurrence of ‘rear-end’, ‘sideswipe’ and ‘head-on’ fatal crashes are 42-times, 35-times and 25-times more than ‘hit pedestrian’ respectively. Similarly, for variable ‘number of vehicle’, likelihood is thrice as ‘single-vehicle’ than ‘two or more vehicles’; and, for variable ‘number of lane’, probability is more on ‘two-lane’ NH-8 than ‘four-lane’ NH-24. Based on the study results, it is recommended to upgrade two-lane (undivided carriageway) to four-lane (divided carriageway) NHs to reduce ‘head-on’ collision.
Acknowledgments
The authors would like to convey thanks to the NHAI and MoRTH for sharing traffic data, and the Police Departments of Haryana, Rajasthan and Uttar Pradesh for providing fatal crash data. The opinions, findings and conclusions expressed here are those of authors.
Disclosure statement
No potential conflict of interest was reported by the authors.