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
Link To Document :
بازگشت