交通信息与安全Issue(1)：78-84,7.DOI:10.3963/j.issn 1674-4861.2016.01.001
基于 BP 神经网络的高速公路事故预测模型∗
An Accident Prediction Model for Expressway Based on BP Neural Network
摘要
Abstract
According to the geometric alignment,traffic volume and accident data of expressway in mountain and hilly areas in China,an accident prediction model is developed based on geometric alignment and traffic volume for expre-ssway segments.A correlation test for geometric features is undertaken by mean impact value.The results show that the features are found to be significant over the test including tangent length,horizontal curve radius,deflection angle,verti-cal curve radius and longitudinal gradient.Accident factors are divided according to the test results.An accident prediction model is developed based on BP neural network.The accuracy of this model reaches 88%,and its applicability on specific expressway segments is verified.The relationship between alignment features and accident rate is verified with sensitivity analysis.The results of model validation show that this model can be applied to all types of expressway segments in mountain and hilly areas with a high accuracy.关键词
交通安全/事故预测模型/高速公路/BP 神经网络/路段单元/预测单元Key words
traffic safety/accident prediction model/expressway/BP neural network/expressway segments/pre-diction factors分类
交通工程引用本文复制引用
邓晓庆,孟祥海,郑来..基于 BP 神经网络的高速公路事故预测模型∗[J].交通信息与安全,2016,(1):78-84,7.基金项目
辽宁省交通运输厅科技项目(201306)资助 （201306）
