Capacity analysis of the pure connected automated vehicle (CAV) traffic remains a challenging problem due to the high-dimensional factors involved in the control design. Especially, the communication loss and communication topology greatly impact the headway variation of CAVs and hence capacity with stochastic properties. This study provides a stochastic framework to mathematically derive multiple factors’ impact including free-flow speed, control gains, communication loss, and traffic arrival pattern on the pure CAV traffic capacity based on a virtual car-following control strategy targeting a single-lane highway and merging section. To begin with, we first mathematically derive the stochastic capacity for a single-lane highway based on a multi-predecessor-based linear feedback and feedforward car-following model for generic stochastic communication loss models. For a further illustration, a detailed analysis is conducted based on a well-known Signal-to-Interference-plus-Noise Ratio (SINR) communication loss model. We then extend the derivation to a merging section by a virtual car-following concept considering traffic arrival pattern’s stochasticity. Numerical sensitivity analyses have been conducted to systematically evaluate the impact of multiple factors mentioned. As the result indicated, the stochastic communication loss and traffic arrival pattern do have a significant impact on the pure CAV traffic capacity of the above scenarios.

由于控制设计中涉及的高维因素，纯联网自动驾驶汽车 (CAV) 交通的容量分析仍然是一个具有挑战性的问题。特别是，通信损耗和通信拓扑极大地影响了 CAV 的车头时距变化，从而影响了具有随机特性的容量。本研究提供了一个随机框架，以基于针对单车道高速公路的虚拟跟驰控制策略，从数学上推导多个因素的影响，包括自由流速度、控制增益、通信损耗和交通到达模式对纯 CAV 交通容量的影响和合并部分。首先，我们首先基于针对通用随机通信损失模型的基于多前驱的线性反馈和前馈跟车模型，从数学上推导出单车道高速公路的随机通行能力。为了进一步说明，基于众所周知的信号干扰加噪声比 (SINR) 通信损耗模型进行了详细分析。然后，我们通过考虑交通到达模式的随机性的虚拟跟车概念将推导扩展到合并路段。已经进行了数值敏感性分析，以系统地评估所提到的多个因素的影响。结果表明，随机通信丢失和交通到达模式确实对上述场景的纯 CAV 交通容量产生重大影响。基于众所周知的信号干扰加噪声比 (SINR) 通信损耗模型进行了详细分析。然后，我们通过考虑交通到达模式的随机性的虚拟跟车概念将推导扩展到合并路段。已经进行了数值敏感性分析，以系统地评估所提到的多个因素的影响。结果表明，随机通信丢失和交通到达模式确实对上述场景的纯 CAV 交通容量产生重大影响。基于众所周知的信号干扰加噪声比 (SINR) 通信损耗模型进行了详细分析。然后，我们通过考虑交通到达模式的随机性的虚拟跟车概念将推导扩展到合并路段。已经进行了数值敏感性分析，以系统地评估所提到的多个因素的影响。结果表明，随机通信丢失和交通到达模式确实对上述场景的纯 CAV 交通容量产生重大影响。已经进行了数值敏感性分析，以系统地评估所提到的多个因素的影响。结果表明，随机通信丢失和交通到达模式确实对上述场景的纯 CAV 交通容量产生重大影响。已经进行了数值敏感性分析，以系统地评估所提到的多个因素的影响。结果表明，随机通信丢失和交通到达模式确实对上述场景的纯 CAV 交通容量产生重大影响。