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A New Method For Urban Traffic State Estimation Based On Vehicle Tracking Algorithm

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4 Author(s)
Yikai Chen ; Shanghai Jiao Tong Univ., Shanghai ; Lingling Gao ; Zhi-peng Li ; Liu, Yun-cai

In this paper, a new method for urban traffic state estimation is proposed. Real-time GPS locational data are collected to implement the vehicle tracking algorithm throughout the urban GIS network. Average velocities along these tracks are calculated and distributed proportionally. By integrating the velocity contributions on each road link, traffic states are finally estimated along rolling time periods. Compared with conventional methods, the proposed method keeps the continuity of vehicle travels and runs quickly without additional data sources. Experiments on real taxi scheduling signals indicate that the new method is both reasonable and practical.

Published in:

Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE

Date of Conference:

Sept. 30 2007-Oct. 3 2007

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