上海交通大学学报

上海交通大学学报（自然版）

• 自动化技术、计算机技术 • 上一篇    下一篇

基于证据融合的实时交通状态估计

孔庆杰，陈宜开，刘允才   

  1. (上海交通大学 电子信息与电气工程学院， 上海 200240)
  • 收稿日期:2007-10-30 修回日期:1900-01-01 出版日期:2008-10-28 发布日期:2008-10-28
  • 通讯作者: 刘允才

RealTime Traffic State Estimation Based on Evidential Fusion

KONG Qing-jie, CHEN Yi-kai, LIU Yun-cai   

  1. (School of Electronic, Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2007-10-30 Revised:1900-01-01 Online:2008-10-28 Published:2008-10-28
  • Contact: LIU Yun-cai

摘要： 为满足智能交通监控系统中融合多种传感器信息综合估计交通状态的需要，把证据理论与联邦滤波器框架相结合，提出了一种联邦证据融合方法，并成功应用于城市交通路网的实时交通状态估计.实例分析表明，利用联邦滤波器的融合结构，把时域信息和传感器的可靠性信息融入融合系统，不但可以克服证据理论不能正确处理冲突证据的缺点，而且能够增强证据融合系统的实时性和鲁棒性.

关键词: 智能交通系统, 交通状态估计, 证据理论, 联邦滤波器

Abstract: In order to estimate traffic states more accurately by fusing multisensors in intelligent traffic surveillance system, this paper presented a federated evidential fusion method, in which the evidence theory and the federated filter are integrated. This method is successfully applied to a real urban traffic network for realtime traffic state estimation. Also it was testified that this approach can not only overcome the drawback that the evidence theory can not deal with conflict exactly, but also enhance the realtime performance and robustness of the evidential fusion system, because the structure of the federated filter makes it possible to combine the temporal information and the reliability of sensors into the fusion system.

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