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Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection

Author

Listed:
  • Dexin Yu
  • Xiujuan Tian
  • Xue Xing
  • Shutao Gao

Abstract

In order to optimize the signal timing for isolated intersection, a new method based on fuzzy programming approach is proposed in this paper. Considering the whole operation efficiency of the intersection comprehensively, traffic capacity, vehicle cycle delay, cycle stops, and exhaust emission are chosen as optimization goals to establish a multiobjective function first. Then fuzzy compromise programming approach is employed to give different weight coefficients to various optimization objectives for different traffic flow ratios states. And then the multiobjective function is converted to a single objective function. By using genetic algorithm, the optimized signal cycle and effective green time can be obtained. Finally, the performance of the traditional method and new method proposed in this paper is compared and analyzed through VISSIM software. It can be concluded that the signal timing optimized in this paper can effectively reduce vehicle delays and stops, which can improve traffic capacity of the intersection as well.

Suggested Citation

  • Dexin Yu & Xiujuan Tian & Xue Xing & Shutao Gao, 2016. "Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-12, March.
    • Handle: RePEc:hin:jnlmpe:1682394
    DOI: 10.1155/2016/1682394
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    Cited by:

    1. Zahra Zeinaly & Mahdi Sojoodi & Sadegh Bolouki, 2023. "A Resilient Intelligent Traffic Signal Control Scheme for Accident Scenario at Intersections via Deep Reinforcement Learning," Sustainability, MDPI, vol. 15(2), pages 1-26, January.
    2. Suhaib Alshayeb & Aleksandar Stevanovic & Nikola Mitrovic & Elio Espino, 2022. "Traffic Signal Optimization to Improve Sustainability: A Literature Review," Energies, MDPI, vol. 15(22), pages 1-24, November.

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