What factors impact injury severity of vehicle to electric bike crashes in China?

Abstract

In place of pedestrians and bikes, crashes involving electric bikes have become a large portion of crashes in China in these years. Crash data from Beijing, China, from the year 2009 to 2015 are used to identify how the factors impact injury severity of vehicle to electric bike crashes. A total of 150 crash samples are collected in order to investigate the influence of human, vehicle, road, and environment characteristics on injury severity. For that reason, a binary logistic model is established to analyze the significance of main contributing factors of crashes. This article describes the sample data, which includes time of incident, road users' age and gender, crash patterns, and characteristics of road and environment. The results of descriptive statistics reveal that older riders and younger drivers are more likely to be involved in fatal crashes; the crashes have much higher frequency in motor vehicle roads, in suburban area, and in roads with higher speed limitation. The logistic regression model shows that older riders (age > 25) and electric bike turning increased the injury severity. On the contrary, the off-peak hour and the older driver (age > 25) of vehicle reduced the likelihood of fatal crash. These findings are hopeful to react on related research for accident prevention and injury reduction.