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An Adaptive Signal Control Method with Optimal Detector Locations

Author

Listed:
  • Senlai Zhu

    (School of Transportation, Nantong University, Nantong 226019, China)

  • Ke Guo

    (JSTI GROUP, Nanjing 210019, China)

  • Yuntao Guo

    (Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA)

  • Huairen Tao

    (School of Transportation, Nantong University, Nantong 226019, China)

  • Quan Shi

    (School of Transportation, Nantong University, Nantong 226019, China)

Abstract

The adaptive traffic signal control system is a key component of intelligent transportation systems and has a primary role in effectively reducing traffic congestion. The high costs of implementation and maintenance limit the applicability of the adaptive traffic signal control system, especially in developing countries. This paper proposes a low-cost adaptive signal control method that is easy to implement. Two detectors are installed in each vehicle lane at an optimal location determined by the proposed method to detect green and red redundancy time, based on which the original signal timing is adjusted through a signal controller. The proposed method is evaluated through case studies with low and high volume-to-capacity ratio intersections. The results show that the proposed adaptive signal control method can significantly reduce total traffic delay at intersections.

Suggested Citation

  • Senlai Zhu & Ke Guo & Yuntao Guo & Huairen Tao & Quan Shi, 2019. "An Adaptive Signal Control Method with Optimal Detector Locations," Sustainability, MDPI, vol. 11(3), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:727-:d:202044
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    References listed on IDEAS

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    1. Lee, Seunghyeon & Wong, S.C. & Varaiya, Pravin, 2017. "Group-based hierarchical adaptive traffic-signal control part I: Formulation," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 1-18.
    2. Silcock, J. P., 1997. "Designing signal-controlled junctions for group-based operation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(2), pages 157-173, March.
    3. Yin, Yafeng, 2008. "Robust optimal traffic signal timing," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 911-924, December.
    4. Lee, Seunghyeon & Wong, S.C. & Varaiya, Pravin, 2017. "Group-based hierarchical adaptive traffic-signal control Part II: Implementation," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 376-397.
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    Cited by:

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    2. Zibin Wei & Tao Peng & Sijia Wei, 2022. "A Robust Adaptive Traffic Signal Control Algorithm Using Q-Learning under Mixed Traffic Flow," Sustainability, MDPI, vol. 14(10), pages 1-16, May.
    3. Arshad Jamal & Muhammad Tauhidur Rahman & Hassan M. Al-Ahmadi & Irfan Ullah & Muhammad Zahid, 2020. "Intelligent Intersection Control for Delay Optimization: Using Meta-Heuristic Search Algorithms," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
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    5. Heqing Tan & Muqing Du & Xiaowei Jiang & Zhaoming Chu, 2019. "The Combined Distribution and Assignment Model: A New Solution Algorithm and Its Applications in Travel Demand Forecasting for Modern Urban Transportation," Sustainability, MDPI, vol. 11(7), pages 1-18, April.

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