The Adaptive Road Routing Recommendation for Traffic Congestion Avoidance in Smart City-Reference-Cited by-同舟云学术

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The Adaptive Road Routing Recommendation for Traffic Congestion Avoidance in Smart City

Published:2013-11-06 Issue:1 Volume:77 Page:225-246
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Cheng Sheng-Tzong,Li Jian-Pan,Horng Gwo-Jiun,Wang Kuo-Chuan

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1007/s11277-013-1502-4.pdf

Reference23 articles.

1. Srinivasan, D., Min Chee, C., & Cheu, R. L. (2006). Neural networks for real-time traffic signal control. IEEE Transactions on Intelligent Transportation Systems, 7(3), 261–272.

2. Sanchez-Medina, J. J., Galan-Moreno, M. J., & Rubio-Royo, E. (2010). Traffic signal optimization in “La Almozara” district in saragossa under congestion conditions, using genetic algorithms, traffic microsimulation, and cluster computing. IEEE Transactions on Intelligent Transportation Systems, 11(1), 132–141.

3. Balaji, P. G., German, X., & Srinivasan, D. (2010). Urban traffic signal control using reinforcement learning agents. Intelligent Transport Systems, 4(3), 177–188.

4. Arel, I., Liu, C., Urbanik, T., et al. (2010). Reinforcement learning-based multi-agent system for network traffic signal control. Intelligent Transport Systems, 4(2), 128–135.

5. Prashanth, L. A., & Bhatnagar, S. (2011). Reinforcement learning with function approximation for traffic signal control. IEEE Transactions on Intelligent Transportation Systems, 12(2), 412–421.

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