交通运输系统工程与信息 ›› 2013, Vol. 13 ›› Issue (6): 52-59.

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基于HMM的交叉口交通事件预测研究

周君*1,程琳2,周凌云1,褚昭明2   

  1. 1. 淮阴工学院 交通学院,江苏 淮安223003;2. 东南大学 交通学院,南京210096
  • 收稿日期:2013-05-02 修回日期:2013-06-05 出版日期:2013-12-24 发布日期:2014-01-14
  • 作者简介:周君(1980-),女,湖南南县人,博士.
  • 基金资助:

    国家自然科学基金(51078085).

Traffic Incident Prediction on Intersections Based on HMM

ZHOU Jun1, CHENG Lin2, ZHOU Ling-yun1, CHU Zhao-ming2   

  1. 1. Faculty of Transportation Engineering, Huaiyin Institute of Technology, Huai’an 223003, Jiangsu,China;2. School of Transportation, Southeast University, Nanjing 210096, China
  • Received:2013-05-02 Revised:2013-06-05 Online:2013-12-24 Published:2014-01-14

摘要:

交叉口是一个交通事故多发区,除了交叉口设计复杂外,更重要的是交叉口车辆行驶情况比较杂乱,使得交叉口交通冲突的检测难度增加.本文以淮安市淮海南路与解放路交叉口为例,根据车辆运行与相位配时总结在该四相位控制的交叉口具有冲突的两辆车的相对运动情况,在车辆跟踪的基础上对具有冲突的车辆进行运动矢量量化,采用HMM(隐马尔可夫模型)对该交叉口的交通冲突进行分类,并通过实验验证该算法能对正常交通下的车辆运行状态进行冲突分类.通过冲突的检测可以提前预测发生在交叉口处的交通事故(如碰撞、追尾、突然停车等)和危险状态.

关键词: 智能交通, 事件预测, 隐马尔可夫模型, 交叉口, 交通冲突

Abstract:

The intersection is an area where many accidents occur. Reasons for accidents are due to complicated intersection designs and the congested travel conditions. For these reasons, traffic incident detection is more complicated. This paper uses the intersections of Huaihai South Road and Jiefang Road as an example. According to the vehicle operation and phase timing, the situations of two vehicle's relative movement on four phase intersections are summarized. The motion vectors of the conflicting vehicle are quantized on the basis of vehicle tracking. Then, the HMM is used to classify the traffic conflicts of the intersection. Finally, numerical experiments verify that the algorithm is able to classify the conflict when the traffic is normal. Furthermore, the algorithm can forecast the traffic accidents (such as bumping, tandem, and stop) which occurred in the intersection.

Key words: intelligent transportation, incident detection, hidden Markov model, intersection, traffic conflict

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