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Using Cellular Automata to Investigate Pedestrian Conflicts with Vehicles in Crosswalk at Signalized Intersection

Author

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  • Xiaomeng Li
  • Xuedong Yan
  • Xingang Li
  • Jiangfeng Wang

Abstract

The operational efficiency and safety of pedestrian flows at intersections is an important aspect of urban traffic. Particularly, conflicts between pedestrians and vehicles in crosswalk are one of the most influential factors for intersection safety. This paper presents a cellular automata model that simulates pedestrian and vehicle crossing behaviors at signalized intersections. Through the simulation, we investigate the effects of different pedestrian signal timing and crosswalk widths on the crosswalk capacity, the number of traffic conflicts between pedestrians and vehicles, and pedestrian delay due to the conflicts. The simulation results indicate that the cellular automata is an effective simulation platform for investigating complex pedestrian-related traffic phenomenon at signalized intersections.

Suggested Citation

  • Xiaomeng Li & Xuedong Yan & Xingang Li & Jiangfeng Wang, 2012. "Using Cellular Automata to Investigate Pedestrian Conflicts with Vehicles in Crosswalk at Signalized Intersection," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-16, November.
    • Handle: RePEc:hin:jnddns:287502
    DOI: 10.1155/2012/287502
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    Cited by:

    1. Li, Xiang & Sun, Jian-Qiao, 2019. "Intersection multi-objective optimization on signal setting and lane assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1233-1246.
    2. Chen, Liang & Sun, Jingjie & Li, Kun & Li, Qiaoru, 2022. "Research on the effectiveness of monitoring mechanism for “yield to pedestrian” based on system dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    3. Farzaneh Montazeri & Fausto Errico & Luc Pellecuer, 2022. "Comparison of the Performance of Hybrid Traffic Signal Patterns and Conventional Alternatives When Accounting for Both Pedestrians and Vehicles," Sustainability, MDPI, vol. 14(20), pages 1-33, October.
    4. Kuang, Xianyan & Chen, Ziru, 2022. "Trajectory research of Cellular Automaton Model based on real driving behaviour," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).

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