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Exploring the impact of damping on Connected and Autonomous Vehicle platoon safety with CACC

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  • Dai, Yulu
  • Yang, Yuwei
  • Wang, Zhiyuan
  • Luo, YinJie

Abstract

Connected and Autonomous Vehicle (CAV) platooning has gained attention for its potential for vastly enhancing capacity and safety of future transport systems. Previous research on CAV platoon control approximates stability as safety during CAV operations and primarily addressed instability and stability properties. Nevertheless, it is vital to note that stability does not stand for absolutely safe, since the behaviors of CAV platoons could also be impacted by the oscillation characteristics of damping that are essential for CAV platoons to boost reliability against variant continuous disturbances. To explore the impact of damping on CAV platoon safety, the time-domain analysis approach is introduced to reveal the relationship between damping characteristics and CAV platoon safety performance with Cooperative Adaptive Cruise Control (CACC) based on the constant time headway policy under stable conditions. Numerical simulations are carried out to verify the impacts of the damping on CAV platoon performance and evaluate the safety of a platoon possessing stability under different damping properties. Further, different control parameters based on damping and stability properties are applied to CAV platoons and their safety is evaluated by calculating the Deceleration Rate to Avoid a Crash (DRAC), Time Exposed Time-to-Collision (TET) and Time-Integrated Time-to-Collision (TIT) as surrogate safety measures of the rear-end collision risk. Numerical analysis results show that it could better maintain platoon safety, when control parameters make the damping ratio between 1 and 1.1.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007397
    DOI: 10.1016/j.physa.2022.128181
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    References listed on IDEAS

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    Cited by:

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    2. Hua, Xuedong & Yu, Weijie & Wang, Wei & Zhao, De, 2023. "Impact of multi-class stochastic cyberattacks on vehicle dynamics and rear-end collision risks for heterogeneous traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).

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