交通运输系统工程与信息 ›› 2014, Vol. 14 ›› Issue (6): 201-206.

• 案例分析 • 上一篇    下一篇

可变信息屏对北京市交通拥堵缓解的评价研究

周洋帆a,贾顺平*a,关伟b,刘爽a   

  1. 北京交通大学a.城市交通复杂系统科学与技术教育部重点实验室;b.交通运输学院,北京100044
  • 收稿日期:2014-06-24 修回日期:2014-10-06 出版日期:2014-12-25 发布日期:2014-12-30
  • 作者简介:周洋帆(1989-),女,河南商丘人,博士生.
  • 基金资助:

    国家自然科学基金重点项目(71131001);国家基础研究计划项目(2012CB725406).

Evaluation on Traffic Congestion Mitigation in Beijing with Variable Message Signs

ZHOU Yang-fana, JIA Shun-pinga, GUANWeib, LIU Shuanga   

  1. a. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology; b. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2014-06-24 Revised:2014-10-06 Online:2014-12-25 Published:2014-12-30

摘要:

可变信息屏(VMS)为缓解大城市交通拥堵提供了一种有效途径,它通过发布诱导信息来均衡路网上的交通需求.为了评价VMS对缓解交通拥堵的效果,本文通过数据挖掘方法建立了一种通用评价模型.所用数据包括由北京市VMS系统和道路检测器得到的VMS历史发布信息和道路交通流数据,这些数据能够真实地反映路网中的交通状况.通过比较诱导信息和提示信息下的拥堵缓解效果,并对不同道路状况下拥堵缓解效果进行时间和空间分析.结果表明,诱导信息能够更加有效地提高拥堵路段的服务水平,特别是严重拥堵路段,诱导信息比提示信息更加有效.

关键词: 智能交通, 交通拥堵, 数据挖掘, 可变信息屏(VMS), 交通诱导

Abstract:

The variable message signs (VMS) provide an effective method to mitigate urban traffic congestion and balance traffic demand through publishing guidance messages. For evaluating the mitigating effect of VMS on congestion, a general-purpose model utilizing the data mining method is developed . The data includes published messages and a large amount of historical traffic flow collected from VMS publishing system and detectors which reflects the most realistic traffic conditions in Beijing road traffic network. Specially, road traffic statuses under two types of messages, guidance message and notice message, are compared to recognize which one is more effective. In the case study, spatial and temporal analyses are introduced separately to evaluate the mitigation of congestion under various traffic conditions. The results indicate that guidance messages on VMS make more significant contributions to improve the level of service of congested roads. Particularly, guidance messages always appeared more effective than notice messages under severe congestion.

Key words: intelligent transportation, traffic congestion, data mining, variable message sign (VMS), traffic guidance

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