Identification of Factors Influencing Crash Severity for Electric Bicycle Using Nondominated Sorting Genetic Algorithm

Abstract

Electric bicycles (E-bike) are one of the most important travel modes in China. In recent years, traffic accidents involving electric bicycles have increased year by year, and research on traffic safety risks of electric bicycles is particularly important. The key factor in obtaining traffic accidents involving electric bicycles is an important basis for the development of electric bicycle traffic management and the relevant policies. Therefore, based on the electric bicycle traffic accident in Hangzhou, this paper uses the nondominated sorting genetic algorithm II (NSGA-II) to study the key factors affecting the severity of electric bicycle accidents. The results show that the type of accident and the type of illegality are the two most important factors affecting the severity of electric bicycle accidents.