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Traffic signal control under stochastic traffic demand and vehicle turning via decentralized decomposition approaches

Author

Listed:
  • Fei, Xinyu
  • Wang, Xingmin
  • Yu, Xian
  • Feng, Yiheng
  • Liu, Henry
  • Shen, Siqian
  • Yin, Yafeng

Abstract

Traffic congestion is a global pressing issue but can be mitigated via effective traffic signal control schemes. In this paper, based on a cell transmission model we coordinate the control of traffic signals at multiple intersections to maximize vehicle throughput on corridors or road networks, under stochastic traffic demand and vehicle turning. We formulate a two-stage stochastic mixed-integer linear program using finite samples of the uncertain parameter, and combine Benders decomposition with the alternating direction method of multipliers to develop spatially-temporally distributed algorithms for optimizing the problem. We test instances of traffic signal control on corridors and grid networks, generated based on synthetic and real-world traffic data. Our results show that (i) considering traffic uncertainty can significantly improve the signal control quality and (ii) decentralized decomposition approaches can quickly find high-quality signal plans for multiple intersections in complex road networks, and fully utilize the computation and communication technologies in smart-transportation infrastructures.

Suggested Citation

  • Fei, Xinyu & Wang, Xingmin & Yu, Xian & Feng, Yiheng & Liu, Henry & Shen, Siqian & Yin, Yafeng, 2023. "Traffic signal control under stochastic traffic demand and vehicle turning via decentralized decomposition approaches," European Journal of Operational Research, Elsevier, vol. 310(2), pages 712-736.
    • Handle: RePEc:eee:ejores:v:310:y:2023:i:2:p:712-736
    DOI: 10.1016/j.ejor.2023.04.012
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    References listed on IDEAS

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    1. Lo, Hong K., 1999. "A novel traffic signal control formulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(6), pages 433-448, August.
    2. Yin, Yafeng, 2008. "Robust optimal traffic signal timing," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 911-924, December.
    3. Li, Li & Jabari, Saif Eddin, 2019. "Position weighted backpressure intersection control for urban networks," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 435-461.
    4. Heydecker, Benjamin, 1987. "Uncertainty and variability in traffic signal calculations," Transportation Research Part B: Methodological, Elsevier, vol. 21(1), pages 79-85, February.
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