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Effects of prediction feedback in multi-route intelligent traffic systems

Author

Listed:
  • Dong, Chuanfei
  • Ma, Xu
  • Wang, Binghong
  • Sun, Xiaoyan

Abstract

We first study the influence of an efficient feedback strategy named the prediction feedback strategy (PFS) based on a multi-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. In this scenario, our model incorporates the effects of adaptability into the cellular automaton models of traffic flow. Simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux. At the end of this paper, we also discuss in what situation PFS will become invalid in multi-route systems.

Suggested Citation

  • Dong, Chuanfei & Ma, Xu & Wang, Binghong & Sun, Xiaoyan, 2010. "Effects of prediction feedback in multi-route intelligent traffic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3274-3281.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:16:p:3274-3281
    DOI: 10.1016/j.physa.2010.02.036
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    Citations

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    Cited by:

    1. Yuhui Guo & Zhiwei Tang & Jie Guo, 2020. "Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    2. Zhang, Zhao-Ze & Huang, Hai-Jun & Tang, Tie-Qiao, 2018. "Impacts of preceding information on travelers’ departure time behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 523-529.
    3. Chen, Bokui & Xie, Yanbo & Tong, Wei & Dong, Chuanfei & Shi, Dongmei & Wang, Binghong, 2012. "A comprehensive study of advanced information feedbacks in real-time intelligent traffic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2730-2739.

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