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Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon

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  • Fan Ding

    (School of Transportation, Southeast University, Nanjing 211189, China
    The first two authors contribute to this paper evenly.)

  • Jiwan Jiang

    (School of Transportation, Southeast University, Nanjing 211189, China
    Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
    The first two authors contribute to this paper evenly.)

  • Yang Zhou

    (Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Ran Yi

    (Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Huachun Tan

    (School of Transportation, Southeast University, Nanjing 211189, China)

Abstract

With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

Suggested Citation

  • Fan Ding & Jiwan Jiang & Yang Zhou & Ran Yi & Huachun Tan, 2020. "Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:9955-:d:452824
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    References listed on IDEAS

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    3. Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    4. Zhou, Yang & Wang, Meng & Ahn, Soyoung, 2019. "Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 69-86.
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    Cited by:

    1. Zhou, Zhi & Li, Linheng & Qu, Xu & Ran, Bin, 2023. "An autonomous platoon formation strategy to optimize CAV car-following stability under periodic disturbance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    2. Dai, Yulu & Yang, Yuwei & Wang, Zhiyuan & Luo, YinJie, 2022. "Exploring the impact of damping on Connected and Autonomous Vehicle platoon safety with CACC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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