数据驱动的偶发拥堵时空建模及传播分析

交通运输系统工程与信息 ›› 2019, Vol. 19 ›› Issue (2): 189-195.

数据驱动的偶发拥堵时空建模及传播分析

韦伟^{*1, 2}，刘岭²，彭其渊¹，陈绍宽³

1. 西南交通大学交通运输与物流学院，成都 610031；2. 北京全路通信信号研究设计院集团有限公司，北京 100073；3. 北京交通大学交通运输学院，北京 100044

收稿日期:2018-10-15 修回日期:2018-11-22 出版日期:2019-04-25 发布日期:2019-04-25
作者简介:韦伟(1989-)，男，贵州清镇人，博士后.
基金资助:
国家重点研发计划/National Key R & D Program of China(2017YFB1200700).

Data-driven Space-time Modeling and Propagation Study of Network-wide Sudden Congestion

WEI Wei^{1, 2}, LIU Ling ², PENG Qi-yuan ¹, CHEN Shao-kuan ³

1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China; 2. Beijing National Railway Research & Design Institute of Signal & Communication Group Co. , Ltd., Beijing 100073, China; 3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Received:2018-10-15 Revised:2018-11-22 Online:2019-04-25 Published:2019-04-25

摘要/Abstract

摘要：

为研究实际的道路交通路网中偶发拥堵的传播和演化特性，充分发挥海量交通流数据的潜在价值，克服现有基于模拟仿真的拥堵分析方法因理论假设和参数设置所导致的 “失真”问题，本文在交通流实测数据的基础上，建立改进的 PLS-STAR模型对偶发拥堵的时空传播结构进行描述，并提出偶发拥堵的直接和间接时空传播效应两种概念对拥堵的时空传播影响进行刻画，从而构造了一种数据驱动的偶发拥堵时空传播效应评估方法.通过北京路网的案例研究发现，路网服务水平的降低，更大程度来源于拥堵传播的间接影响而非直接取决于突发的交通量增加，因此，通过控制拥堵传播来提升城市路网的服务水平仍具有巨大潜力.

关键词: 智能交通, 偶发拥堵, 数据驱动, 时空建模, 传播特性

Abstract:

For further analyzing the propagation and evolution characteristics of sudden congestion in actual road network, eliminating the distortion problem commonly existing in traditional simulation-based method because of superfluous assumptions or parameters, and taking advantage of the oceans of traffic flow data, an improved PLSSTAR model is developed to characterize the complex space-time propagation structure of sudden congestion on the basis of analyzing and identifying the sudden disruption using real traffic flow data. Then a congestion propagation effect evaluation method based on PLS-STAR is proposed based on the direct and indirect effects of space-time congestion propagation. By case studies on the road network in Beijing, it can be concluded that the reduction of road network’s service level is more attributed to the indirect effect of traffic congestion propagation, rather than the sudden increase of traffic volume. Therefore, there is still great potential to improve the service level of the urban road network by controlling congestion propagation effect.

Key words: intelligent transportation, sudden congestion, data-driven study, space-time modeling, propagation characteristic

中图分类号:

U491

韦伟，刘岭，彭其渊，陈绍宽. 数据驱动的偶发拥堵时空建模及传播分析[J]. 交通运输系统工程与信息, 2019, 19(2): 189-195.

WEI Wei, LIU Ling, PENG Qi-yuan, CHEN Shao-kuan. Data-driven Space-time Modeling and Propagation Study of Network-wide Sudden Congestion[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(2): 189-195.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19818.shtml

http://www.tseit.org.cn/CN/Y2019/V19/I2/189

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