Particle Filter for Estimating Freeway Traffic State in Beijing
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-27
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Bi, Jun& Chang, Can& Fan, Yang. 2013. Particle Filter for Estimating Freeway Traffic State in Beijing. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1009186
Modern Language Association (MLA)
Bi, Jun…[et al.]. Particle Filter for Estimating Freeway Traffic State in Beijing. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1009186
American Medical Association (AMA)
Bi, Jun& Chang, Can& Fan, Yang. Particle Filter for Estimating Freeway Traffic State in Beijing. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1009186
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009186