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Cellular automata model for traffic flow at intersections in internet of vehicles

Author

Listed:
  • Zhao, Han-Tao
  • Liu, Xin-Ru
  • Chen, Xiao-Xu
  • Lu, Jian-Cheng

Abstract

Considering the effect of the front vehicle’s speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

Suggested Citation

  • Zhao, Han-Tao & Liu, Xin-Ru & Chen, Xiao-Xu & Lu, Jian-Cheng, 2018. "Cellular automata model for traffic flow at intersections in internet of vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 40-51.
    • Handle: RePEc:eee:phsmap:v:494:y:2018:i:c:p:40-51
    DOI: 10.1016/j.physa.2017.11.152
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    Citations

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    Cited by:

    1. Wang, Jinghui & Lv, Wei & Jiang, Yajuan & Qin, Shuangshuang & Li, Jiawei, 2021. "A multi-agent based cellular automata model for intersection traffic control simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    2. Cui, Nan & Chen, Bokui & Zhang, Kai & Zhang, Yi & Liu, Xiaotong & Zhou, Jun, 2019. "Effects of route guidance strategies on traffic emissions in intelligent transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 32-44.
    3. Hua, Wei & Yue, Yixiang & Wei, Zhenlin & Chen, Jianhua & Wang, Wenrong, 2020. "A cellular automata traffic flow model with spatial variation in the cell width," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    4. Ding, Zhongjun & Chen, Bokui & Zhang, Lele & Jiang, Rui & Wu, Yao & Ding, Jianxun, 2019. "Segment travel time route guidance strategy in advanced traveler information systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    5. Li, Haijian & Zhang, Junjie & Sun, Xiaoliang & Niu, Jun & Zhao, Xiaohua, 2022. "A survey of vehicle group behaviors simulation under a connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    6. Wang, Jie & Cai, Zhiyu & Chen, Yaohui & Yang, Peng & Chen, Bokui, 2023. "An advanced control strategy for connected autonomous vehicles based on Micro simulation models at multiple intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    7. Jiang, Yangsheng & Wang, Sichen & Yao, Zhihong & Zhao, Bin & Wang, Yi, 2021. "A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).

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