【作者】 李康；

【导师】 钱大琳；

【作者基本信息】 北京交通大学 ， 安全科学与工程， 2017， 硕士

【摘要】 高速公路具有快速、封闭、全立交的交通控制方式的特点,为车辆行驶提供了良好的条件,高速公路的快速发展大大改善了我国的交通出行情况,同时为我国经济社会建设提供了有利支持。然而,随着高速公路里程的快速增长,交通事故也显著增加,虽然近年来我国高速公路交通事故状况得到了较大的改善,但高速公路交通事故仍然对人民的生命和财产安全造成了严重危害。因此,对高速公路交通事故进行深入分析,对于提高高速公路行车安全,预防和减少交通事故的发生具有重要意义。本文首先基于对高速公路事故分布规律的研究方法,依据已有的高速公路事故数据资料同国外对高速公路交通事故的分布规律进行对比分析,应用统计分析方法,分析高速公路交通事故的时间分布规律、气候分布规律、事故形态分布规律和车型分布规律,得出我国高速公路交通事故的特征。随后本文分析了高速公路交通系统运行中人、车、道路、环境四个因素与交通事故的关系,并针对事故信息高维度、非线性的特点,选用支持向量机算法进行事故严重程度分析研究。应用支持向量机算法构建分类模型,对整理得到的高速公路交通事故数据进行研究,将事故严重程度按照二分类方法建立非线性SVM模型。最后,本文将收集到的高速公路交通事故按事故车辆类型进行分类,分为客车事故、客车-货车事故和货车事故,在分类建模过程中,针对整个事故数据库和三个分类分别建立相应的贝叶斯网络,以期探索在不同车辆类别中潜在的交通事故规律。引入五项指标:正确率、灵敏度、特异度、敏感性和特异性调和平均值(HMSS)指标,并应用ROC曲线对建立的贝叶斯网络模型分类效果进行评价,随后研究贝叶斯网络结构学习的结果得出了各事故影响变量在不同的分类中的不同依赖关系。更多还原

【Abstract】 Highway,with high speed,enclosed type,and whole fly-over design as remarkable characteristics,creates various advantages to vehicle traveling.Rapid development of highway not only improves directly traffic status quo at home,but offers strong support to China economic construction.Nevertheless,there is a trend that increasing traffic accidents unavoidably go with fast growing of highway mileage.In spite of being gradually decreased in quantity,highway traffic accidents are still serious threat to people’s life and property safety.Therefore,deep analysis for highway traffic accidents is of great significance to strengthen traffic safety on highway,thus reducing or avoiding traffic accidents.This paper,based on research on distribution regularities of highway traffic accidents,contrastive analysis to present specific accident data and overseas study achievements on distribution regularities of highway accidents,with help of statistical analysis method,researches distribution regularities of highways accidents in time,climate,accident type and vehicle type,thereby working out remarkable characteristics of China highway traffic accidents.Further,this paper makes analysis of relationship between traffic accidents and four factors operating in a highway traffic system,that is,people,vehicle,roadway and environment,and then,makes analytical study on accident severity with support vector machines(SVM)algorithm,the selection of which is based on accident information’s specialty of high dimension and nonlinearity.Trough application of SVM algorithm on building disaggregated model,this paper explores the collected data of highway traffic accidents,differentiating accident severity according to binary classification methods,thereby establishing non-linear SVM model.Last,this paper divides the vehicle involved in the collected highway traffic accidents into bus and coach accident,Coach-truck accident and truck accident.This paper introduces five index during the process of model building,namely,accuracy、sensitivity、specificity、Harmonic Mean of Sensitivity and Specificity(HMSS),to make effect evaluation to Bayesian Network analysis,and meanwhile,make clustering effect evaluation by using Receiver Operating Characteristic(ROC)curve.Corresponding Bayesian Networks are finally built directing at the whole accident database and three clusters.Study on structure of Bayesian Network helps to work out dependency relationships between accident influential variables under different clusters.更多还原