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Modeling and simulation of lane-changing and collision avoiding autonomous vehicles on superhighways

Author

Listed:
  • He, Yongming
  • Feng, Jia
  • Wei, Kun
  • Cao, Jian
  • Chen, Shisheng
  • Wan, Yanan

Abstract

Collision avoidance during vehicle lane-changing was studied using modeling simulation verification method to solve the problem of collision of vehicles on superhighways. The lateral acceleration model and the collision avoidance minimum safety spacing model were established based on the theoretical analysis of the quintic polynomial lane-changing trajectory model. Additionally, the simulated minimum safety spacing of collision avoidance was calculated using vehicle speed and lane-changing time. The simulation scene was divided into general and emergency lane-changing scenarios under the condition of limiting the maximum lateral acceleration, and the simulation scenarios were subdivided into seven simulation scenarios according to different lane-changing times and road widths for simulation verification. The results demonstrated that a longer lane-changing time was selected in the general lane-changing scenario, and the lateral acceleration and swing angle speed of the vehicle decrease with the increase of the lane-changing time. This ensured collision avoidance, stable vehicle driving, and comfort and safety of passengers. The minimum safety spacing and lane-changing time were short in the emergency lane-changing scenario, and the vehicle exhibited a mild skidding phenomenon during the lane-changing. However, rollover did not occur, which ensured collision avoidance. The distances between the vehicles after the lane avoidance simulation were 4.87, 5.06, 6.89, 6.49, 7.76, 4.21, and 5.52 m, respectively. It demonstrated that the seven lane-changing and avoidance simulation models involved in this paper had good effect on vehicle collision avoidance. The effectiveness and accuracy of the steering collision avoidance of autonomous vehicles on superhighways are verified using the simulation platform, which can effectively improve the safety of superhighway driving.

Suggested Citation

  • He, Yongming & Feng, Jia & Wei, Kun & Cao, Jian & Chen, Shisheng & Wan, Yanan, 2023. "Modeling and simulation of lane-changing and collision avoiding autonomous vehicles on superhighways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    • Handle: RePEc:eee:phsmap:v:609:y:2023:i:c:s037843712200886x
    DOI: 10.1016/j.physa.2022.128328
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    References listed on IDEAS

    as
    1. Li, Linheng & Wang, Can & Zhang, Ying & Qu, Xu & Li, Rui & Chen, Zhijun & Ran, Bin, 2022. "Microscopic state evolution model of mixed traffic flow based on potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. He, Yongming & Kang, Jia & Pei, Yulong & Ran, Bin & Song, Yuting, 2021. "Research on influencing factors of fuel consumption on superhighway based on DEMATEL-ISM model," Energy Policy, Elsevier, vol. 158(C).
    3. Li, Linheng & Gan, Jing & Zhou, Kun & Qu, Xu & Ran, Bin, 2020. "A novel lane-changing model of connected and automated vehicles: Using the safety potential field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
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    Cited by:

    1. Wenjin Sun & Yongjun Min, 2023. "Research on a Driving Assistance System for Lane Changes on Foggy Highways," Sustainability, MDPI, vol. 15(13), pages 1-20, June.

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