DocumentCode
2963757
Title
Dynamic estimation of freeway origin-destination demand and travel time using extended Kalman filtering algorithm
Author
Hu, Shou-Ren ; Chen, Chi-Bang
Author_Institution
Dept. of Transp. Manage., Tamkang Univ., Taipei, Taiwan
Volume
2
fYear
2004
fDate
2004
Firstpage
1329
Abstract
In the present research, a nonlinear Kalman filtering approach, i.e., extended Kalman filter (EKF) was proposed to solve dynamic OD flows and travel times on a freeway segment. The non-linearity results from the facts that the coefficient matrices in the measurement equation of the Kalman filtering framework are unknown in advance and needed to be obtained/updated in light of the most recent observations. The numerical results demonstrated the capability of the proposed EKF model in the dynamic estimation of freeway OD demands and travel times. More significantly, one can design beneficial traffic control and management strategies in accordance with the estimation results.
Keywords
Kalman filters; control system synthesis; filtering theory; matrix algebra; traffic control; Kalman filtering algorithm; coefficient matrices; dynamic estimation; freeway origin-destination demand; traffic control; travel times; Bayesian methods; Current measurement; Filtering algorithms; Kalman filters; Least squares approximation; Maximum likelihood estimation; Nonlinear equations; State estimation; Traffic control; Transportation;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2004 IEEE International Conference on
ISSN
1810-7869
Print_ISBN
0-7803-8193-9
Type
conf
DOI
10.1109/ICNSC.2004.1297140
Filename
1297140
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