华南理工大学学报(自然科学版) ›› 2008, Vol. 36 ›› Issue (10): 47-50,56.

• 交通运输工程 • 上一篇    下一篇

基于浮动车技术的动态交通拥挤预测模型

黄玲 徐建闽   

  1. 华南理工大学 土木与交通学院, 广东 广州 510640
  • 收稿日期:2007-09-07 修回日期:1900-01-01 出版日期:2008-10-25 发布日期:2008-10-25
  • 通信作者: 黄玲(1979-),女,博士,讲师,主要从事智能交通系统研究. E-mail:hling@seut.edu.cn
  • 作者简介:黄玲(1979-),女,博士,讲师,主要从事智能交通系统研究.
  • 基金资助:

    国家自然科学基金资助项目(50578064)

Dynamic Traffic Congestion Prediction Model Based on Probe Vehicle Technology

Huang Ling  Xu Jian-min   

  1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2007-09-07 Revised:1900-01-01 Online:2008-10-25 Published:2008-10-25
  • Contact: 黄玲(1979-),女,博士,讲师,主要从事智能交通系统研究. E-mail:hling@seut.edu.cn
  • About author:黄玲(1979-),女,博士,讲师,主要从事智能交通系统研究.
  • Supported by:

    国家自然科学基金资助项目(50578064)

摘要: 提出了一种新的动态交通拥挤预测模型.该模型应用浮动车数据判断路网实时交通流的具体状况,并结合路网静态拓扑结构,应用多重模糊推理,对路段发生交通拥挤的可能性、拥挤程度和形成时间做出预测.现场实测数据表明,该模型具有良好的预测效果.

关键词: 交通拥挤预测, 交通短期预测, 浮动车技术, 智能交通系统

Abstract:

This paper proposes a new dynamic traffic congestion prediction model. In this model, the probe vehicle data are used to estimate the real-time traffic flow situtation in the road network, and the static topology structure of the road network is combined with the multiple fuzzy inferences to predict the possibility, degree and occurrence of traffic congestion. Practical data show that the proposed model is of high prediction accuracy.

Key words: traffic congestion prediction, short-term traffic forecast, probe vehicle technology, intelligent transportation system