交通运输系统工程与信息 ›› 2018, Vol. 18 ›› Issue (5): 75-81.

• 智能交通系统与信息技术 • 上一篇    下一篇

基于在线地图交通态势分析的路网拥堵状态识别

张建旭*,郭力玮   

  1. 重庆交通大学 运输学院,重庆 400074
  • 收稿日期:2018-05-15 修回日期:2018-07-15 出版日期:2018-10-25 发布日期:2018-10-26
  • 作者简介:张建旭(1979-),男,河南长葛人,副教授,博士.
  • 基金资助:

    重庆市社会事业与民生保障科技创新专项/Scientific and Technical Innovation Special Project of Chongqing Social Undertaking and People’s Wellbeing Guarantee (cstc2015shms-ztzx30013);国家自然科学基金(青年)/ National Natural Science Foundation of China (61703064).

Congestion Status Recognition of Road Network Based on Traffic Situation Analysis of Online Map

ZHANG Jian-xu, GUO Li-wei   

  1. School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2018-05-15 Revised:2018-07-15 Online:2018-10-25 Published:2018-10-26

摘要:

为了实现道路网实时拥堵状态识别,以在线地图的历史延时指数为基础,用相邻路段有效拥堵状态发生时间顺序、持续时间阈值和流向流量关系识别传播性拥堵,用拥堵发生频率和持续时间阈值识别单路段系统拥堵,由此确定特定周期内的系统拥堵路段集合Nmax.以其集合范围内相邻路段时刻t的延时指数,以及其邻近拥堵持续时期的皮尔逊相关系数计算传播性系统拥堵程度值DtS;以非传播路段时刻t延时指数计算DtS?;综合前两者得到路网系统拥堵综合程度DtN,并找出该周期内的极限拥堵程度量化值.用Nmax内路段实时延时指数和实时拥堵路段数与极限拥堵状态对应的数值进行比较,计算实时拥堵程度的量化值.经实验证明,该方法能够反映路网系统拥堵形成的规律,实现路网实时拥堵状态的快速识别.

关键词: 交通工程, 在线地图, 延时指数, 路网系统拥堵, 实时拥堵状态识别

Abstract:

In order to realize the real-time congestion status recognition of road network, based on the historical travel delay index of online maps, this paper identifies the transmitted congestion with the time sequence, duration threshold and the relation to traffic movements and flow in the effective congestion state of adjacent sections, and identifies the system congestion of the single section with the threshold of frequency and duration of congestion. Accordingly, the collection Nmax of system congestion sections in a specific period is determined. Calculate the degree of the transmitted system congestion by using the travel delay index at the time t of the adjacent sections and the Pearson correlation coefficient of the duration of its adjacent congestion during its collection range; Calculate Dt S? by the travel delay index at the time t of non-transmitted congestion sections. Combine the former two to get the comprehensive degree DtN of road network system congestion, and find the degree of ultimate congestion within this period. The real-time travel delay index of sections and the number of real-time congested sections in N max are compared with the corresponding values of ultimate congestion state to calculate the degree of the realtime congestion. The experiment shows that this method can reflect the formation regularities of road network system congestion, and realize the rapid recognition of real-time congestion status of road network.

Key words: traffic engineering, online map, travel delay index, road network system congestion, real- time congestion status recognition

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