Highway Abnormal State Detection Based on
Support Vector Machine (SVM)

doi:10.3969/j.issn.1674-0696.2019.05.01

Abstract

Abstract: Aiming at the abnormal state caused by expressway accidents, the detection program of expressway abnormal states on the basis of support vector machine (SVM) was proposed. Firstly, the vehicle breakdown accident model at one-way three-lane basic section of Kun-Yu Expressway was established by VISSIM simulation software and the abnormal events under different conditions were simulated; furthermore, the influence of abnormal states on the traffic capacity of highway section was analyzed. Then, based on SVM model, the abnormal state detection model of expressway was established, and the difference between unilateral and bilateral input was analyzed. The results of the simulation demonstrate that: the established SVM model for detection of abnormal states has good comprehensive performance; with unilateral input, it can also provide satisfactory detection results of the occurrence of abnormal states.

Key words: traffic engineering, highway, event detection, VISSIM simulation, support vector machine

摘要： 针对意外事件所引发的高速公路异常状态，提出了基于支持向量机模型的高速公路异常状态检测方案。首先应用VISSIM仿真软件建立了昆玉高速单向三车道基本路段的车辆抛锚事故模型；对不同条件下的异常事件进行了仿真，并分析了异常状态对高速断面通行能力的影响；然后基于支持向量机模型建立了高速公路异常状态检测模型，分析单侧与双侧输入差异。仿真结果表明：所建立的支持向量机异常状态检测模型综合性能较好，单侧输入也可以较好地检测异常状态的发生。

关键词: 交通工程, 高速公路, 事件检测, VISSIM仿真, 支持向量机

CLC Number:

U491.3

SUN Jingyi1, MOU Ruojin2, SU Xiaobo3. Highway Abnormal State Detection Based on Support Vector Machine (SVM)[J]. Journal of Chongqing Jiaotong University(Natural Science), 2019, 38(05): 1-7.

孙静怡1，牟若瑾2，苏晓波3. 基于支持向量机的高速公路异常状态检测[J]. 重庆交通大学学报（自然科学版）, 2019, 38(05): 1-7.

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Highway Abnormal State Detection Based on Support Vector Machine (SVM)

基于支持向量机的高速公路异常状态检测

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