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Parallel spatiotemporal slot-based heterogeneous vehicle hybrid coordinating method at intersections under intelligent network environment

Author

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  • Chai, Linguo
  • Liu, Xiangyan
  • ShangGuan, Wei
  • Wang, Jian
  • Cai, Baigen

Abstract

Heterogeneous vehicles, which are with a mix of connected and automated vehicles (CAVs) and human pilot vehicles (HPVs), will move on the road together under intelligent network environment. Technologies such as V2X communication can assist vehicle decision-making through hazard warnings and behaviour suggestions. This means that a safer and more efficient control strategy for vehicle operation at intersections can be realized. This paper proposes a parallel spatiotemporal slot-based intersection coordinating method to better coordinate the mixed traffic at intersections. Remaining conflicting times (RCTs) are adopted to form parallel spatiotemporal slots. The Predicted Entering Rhombus with Interval Occupancy Demand (PERIOD) method is proposed to generate a period for each vehicle to pass through an intersection by searching for an optimized time rhombus in parallel spatiotemporal slots. The Acceleration Dynamic Judgement by Utilizing Spatiotemporal Trajectory (ADJUST) method for CAVs and the Signal Interval Generating with Needed Accrediting Latency (SIGNAL) method for HPVs are proposed to control incoming vehicles passing through an intersection within a time period. To verify the performance of the proposed methods, a simulation environment was established. Simulated experiments included different inputs, different CAV rates, different safe headways, different numbers of intersections and different control methods. The results show that the proposed methods can safely coordinate traffic with a safe headway of 2 s. The proposed method can reduce the average delay by 39.2% compared to signal control, and it is better than the BATH and FARE intelligent coordinating methods in heavy traffic. The proposed methods are applied to heavy traffic with an input of 1350 vhc/h in each direction, and the average vehicle delay can be reduced to 27 s. Multiple intersection scenario simulations have been conducted, and the average delay is approximately 16 s.

Suggested Citation

  • Chai, Linguo & Liu, Xiangyan & ShangGuan, Wei & Wang, Jian & Cai, Baigen, 2023. "Parallel spatiotemporal slot-based heterogeneous vehicle hybrid coordinating method at intersections under intelligent network environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
  • Handle: RePEc:eee:phsmap:v:628:y:2023:i:c:s0378437123006817
    DOI: 10.1016/j.physa.2023.129126
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    References listed on IDEAS

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    1. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
    2. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Modeling connected and autonomous vehicles in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 269-277.
    3. Sheu, Jiuh-Biing & Ritchie, Stephen G., 2001. "Stochastic modeling and real-time prediction of vehicular lane-changing behavior," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 695-716, August.
    4. Dion, Francois & Rakha, Hesham & Kang, Youn-Soo, 2004. "Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 99-122, February.
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