Stochastic adaptive control model for traffic signal systems |
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| Institution: | 1. Cosys, Grettia, Ifsttar, 25 allée des Marronniers, Versailles 78000, France;2. PSL, Université Paris-Dauphine, Lamsade, Place du Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France;1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan 153-8505;2. Nagoya Railroad Co., Ltd, Nagoya, Aichi, Japan 450-8501;3. East Nippon Expressway Co., Ltd., Yokohama, Kanagawa, Japan 385-0022;4. Graduate School of Information Sciences, Tohoku University, Sendai, Miyagi, Japan 980-8579;1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao''an Road, Shanghai, PR China;2. University of Michigan Transportation Research Institute (UMTRI), 2901 Baxter Rd, Ann Arbor, MI, 48109, USA;3. Department of Civil and Environmental Engineering, University of Michigan, 2320 G.G. Brown, 2350 Hayward Street, Ann Arbor, MI, USA |
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| Abstract: | An adaptive control model of a network of signalized intersections is proposed based on a discrete-time, stationary, Markov decision process. The model incorporates probabilistic forecasts of individual vehicle actuations at downstream inductance loop detectors that are derived from a macroscopic link transfer function. The model is tested both on a typical isolated traffic intersection and a simple network comprised of five four-legged signalized intersections, and compared to full-actuated control. Analyses of simulation results using this approach show significant improvement over traditional full-actuated control, especially for the case of high volume, but not saturated, traffic demand. |
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