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Mathematical Problems in Engineering
Volume 2013, Article ID 382042, 6 pages
Research Article

Particle Filter for Estimating Freeway Traffic State in Beijing

1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA

Received 15 July 2013; Revised 10 October 2013; Accepted 24 October 2013

Academic Editor: Wuhong Wang

Copyright © 2013 Jun Bi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Freeway traffic state estimation is useful for intelligent traffic guidance, control, and management. The freeway traffic state is featured with rapid and dramatic fluctuations, which presents a strong nonlinear feature. In theory, a particle filter has good performance in solving nonlinear problems. This paper proposes a particle filter based approach to estimate freeway traffic state. The freeway link between the west of Peace Bridge and the west of San Yuan Bridge of the third ring in Beijing is used as the experimental object. According to the traffic characteristics and measurement mode of the link, the second-order validated macroscopic traffic flow model is adopted to set up the link model. The implementation steps of the particle filter for freeway traffic state estimation are described in detail. The estimation error analysis for the experiments proves that the proposed approach has an encouraging estimation performance.