Research on Accident Prediction of Intersection and Identification Method of Prominent Accident Form Based on Back Propagation Neural Network

摘要：

This paper introduces an intersection accident prediction model by applying BP neural network, which can well structure the corresponding function of intersection traffic conditions and accident form, and the paper trains and predicts the model with 197 intersection data, the test results show that the prediction accuracy can reach up to 89 percent. The paper establishes an identification method of accidentprone form according to the protrusion theory on the basis of the prediction result of accident number of sub accident form, which can provide basis for intersection adaption reconstruction.

关键词： accident prediction accident-prone type BP neural network three layers preceptor protrusion theory

作者: Lv Yuejing Zhang Haixia Zhou Xing-lin Liu Ming Li Jie

作者单位: Collge of Automhbile and Traffic Engineering Wuhan University of Science and Technology Wuhan, Hubei Highway School, Changan University, P.R.China, 710064 College of Automobile and Traffic Engineering Wuhan University of Science and Technology Wuhan, Chin Central & Southern China Municipal Design Institute Wuhan, Hubei, 430010, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 434-438

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）