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<p>Connected automated vehicles (CAVs) are essential for future intelligent transportation systems and will coexist with human-driven vehicles on roads. To accurately characterize the behavior of CAVs, real-world data are utilized as the trajectory information of the lead vehicle, and a trajectory simulation is conducted using the adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) models proposed by the PATH laboratory. The simulated vehicle trajectories indicate problems such as collisions, reversing behaviors, and large speed fluctuations. To address these shortcomings, a time-varying desired spacing is introduced into the ACC model to produce the time-varying ACC (TV-ACC) model. Considering the differences between the CACC and ACC, a time-varying desired spacing is incorporated in conjunction with velocity and acceleration information from multiple preceding vehicles into the CACC model to propose the TV-CACC model. Numerical simulations and theoretical derivations demonstrate that compared to the original models, the improved models can overcome deficiencies such as collisions, reversing behaviors, and large speed fluctuations, exhibiting better performance. The improved models exhibit enhanced stability and ride comfort in traffic flow. Increasing the CAVs penetration rate gradually improves the stability and ride comfort in mixed traffic. The stability of mixed traffic flow deteriorates as the maximum platoon size of CAVs increases.</p>

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ACC/CACC Vehicle Car-Following Model Based on a Time-Varying Expected Spacing and a Stability Analysis of Mixed Traffic Flow

  • 期刊论文

  • 发表日期：

    2025年3月3日

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  • Hongxing Zhao,
  • Shuying Liu,
  • Ruiyan Liang,
  • Ruichun He

摘要

Connected automated vehicles (CAVs) are essential for future intelligent transportation systems and will coexist with human-driven vehicles on roads. To accurately characterize the behavior of CAVs, real-world data are utilized as the trajectory information of the lead vehicle, and a trajectory simulation is conducted using the adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) models proposed by the PATH laboratory. The simulated vehicle trajectories indicate problems such as collisions, reversing behaviors, and large speed fluctuations. To address these shortcomings, a time-varying desired spacing is introduced into the ACC model to produce the time-varying ACC (TV-ACC) model. Considering the differences between the CACC and ACC, a time-varying desired spacing is incorporated in conjunction with velocity and acceleration information from multiple preceding vehicles into the CACC model to propose the TV-CACC model. Numerical simulations and theoretical derivations demonstrate that compared to the original models, the improved models can overcome deficiencies such as collisions, reversing behaviors, and large speed fluctuations, exhibiting better performance. The improved models exhibit enhanced stability and ride comfort in traffic flow. Increasing the CAVs penetration rate gradually improves the stability and ride comfort in mixed traffic. The stability of mixed traffic flow deteriorates as the maximum platoon size of CAVs increases.