基于贝叶斯网络的高速公路交通事故研究

发布时间：2018-09-10 18:40

【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。
[Abstract]:Expressway has the characteristics of fast, closed, all-interchange traffic control mode, which provides a good condition for vehicle driving. The rapid development of freeway has greatly improved the traffic travel situation in our country. At the same time for our country's economic and social construction to provide favorable support. However, with the rapid increase of highway mileage, traffic accidents have also increased significantly, although the situation of expressway traffic accidents in China has been greatly improved in recent years. But the highway traffic accident still caused the serious harm to the people's life and property safety. Therefore, it is of great significance to analyze the expressway traffic accidents in order to improve the safety of expressway and to prevent and reduce the occurrence of traffic accidents. First of all, based on the research method of expressway accident distribution law, according to the existing expressway accident data and foreign highway traffic accident distribution law are compared and analyzed, the statistical analysis method is applied. The characteristics of expressway traffic accidents in China are obtained by analyzing the time distribution law, climate distribution law, accident form distribution law and vehicle type distribution law of expressway traffic accidents. Then, this paper analyzes the relationship between human, vehicle, road and environment in expressway traffic system operation and traffic accidents, and aims at the characteristics of high dimensional and nonlinear accident information. Support vector machine (SVM) algorithm is used to analyze the severity of accidents. The classification model is constructed by using support vector machine (SVM) algorithm, and the traffic accident data collected from expressway are studied, and the nonlinear SVM model is established according to the two classification method. Finally, the traffic accidents collected in this paper are classified according to the types of vehicles, which are divided into bus accidents, bus-truck accidents and truck accidents, and in the process of classification and modeling, The corresponding Bayesian network is established for the whole accident database and the three categories in order to explore the potential traffic accident law in different vehicle categories. Five indexes are introduced: correct rate, sensitivity, specificity, sensitivity and specificity harmonic mean (HMSS) index. The classification effect of the established Bayesian network model is evaluated by using ROC curve. Then, the results of Bayesian network structure learning show the different dependencies of each accident impact variable in different classification.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.3

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