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

被引:0
|
作者
Xu, Cheng [1 ,2 ]
机构
[1] Zhejiang Police Coll, Dept Traff Management Engn, Hangzhou 310053, Peoples R China
[2] Zhejiang Univ, Inst Intelligent Transportat Syst, Hangzhou 310058, Peoples R China
来源
基金
中国博士后科学基金;
关键词
E-BIKE; RISK;
D O I
10.1007/978-981-13-8683-1_11
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
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页码:103 / 111
页数:9
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