Factors Affecting Electric Bicycle Rider Injury in Accident Based on Random Forest Model

被引：0
|
作者：
Li Y.-S. [1 ]
Zhang X. [2 ]
Wang W.-J. [1 ]
Ju X.-F. [1 ]
机构：
[1] School of Transportation Engineering, Nanjing Tech University, Nanjing
[2] College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2021年 / 21卷 / 01期
关键词：
Accident injury degree; Electric bicycles; Impact factors; Random forest; Traffic engineering;
D O I：
10.16097/j.cnki.1009-6744.2021.01.030
中图分类号：
学科分类号：
摘要：
This study analyzed the crucial factors that affect the injury degree of electric bicycle riders in the accident and ranked the factors based on their significance. The study collected electric bicycle traffic accident data in a city from 2013 to 2015, and then performed the descriptive statistical analysis. 22 factors related to the severity of traffic accidents were selected for analysis. The random forest model was used to predict the severity of electric bicycle rider injuries, and then rank the significance of the impact factors. The result indicates that the most significant factors affecting the severity of electric bicycle rider injuries in the accident are as follows: the type of accident, the injury is on which part of the body, and the separation type on the road, etc. The study also puts forward suggestions to improve bicycle rider's safety in terms of related factors, which provide reference for prevention of electric bicycle accident and relevant decision-makings in the safety management. Copyright © 2021 by Science Press.
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页码：196 / 200
页数：4
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