Being one of the most promising applications enabled by connected and automated vehicles (CAV) technology, Cooperative Adaptive Cruise Control (CACC) is expected to be deployed in the near term on public roads.} Thus far, the majority of the CACC studies have been focusing on the overall network performance with limited insights on the potential impacts of CAVs on human-driven vehicles (HVs).This paper aims to quantify such impacts by studying the high-resolution vehicle trajectory data that are obtained from microscopic simulation. Two platoon clustering strategies for CACC- an ad hoc coordination strategy and a local coordination strategy-are implemented. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. According to the two-sample Kolmogorov-\textcolor{re}{Smirnov} test, however, the distributions of the hard braking events (as a potential safety impact) for HVs change significantly under local coordination strategy. For both of the clustering strategy, CAVs increase the average lane change frequency for HVs. The break-even point for average lane change frequency between the two strategies is observed at 30% MPR, which decreases from 5.42 to 5.38 per vehicle. The average lane change frequency following a monotonically increasing pattern in response to MPR, and it reaches the highest 5.48 per vehicle at 40% MPR. Lastly, the interaction state of the car-following model for HVs is analyzed. It is revealed that the composition of the interaction state could be influenced by CAVs as well. One of the apparent trends is that the time spent on approaching state declines with the increasing presence of CAVs.

中文翻译：

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CAV聚类策略对混合交通流特征的影响：车辆轨迹数据分析

作为互联和自动驾驶汽车 (CAV) 技术支持的最有前途的应用之一，协同自适应巡航控制 (CACC) 有望在近期内部署在公共道路上。}到目前为止，大多数 CACC 研究都是专注于整体网络性能，而对 CAV 对人类驾驶车辆 (HV) 的潜在影响的了解有限。本文旨在通过研究从微观模拟中获得的高分辨率车辆轨迹数据来量化此类影响。实施了 CACC 的两个排集群策略——临时协调策略和本地协调策略。结果表明，就网络吞吐量和生产力而言，本地协调优于所有测试市场渗透率 (MPR) 的临时协调。然而，根据两样本 Kolmogorov-\textcolor{re}{Smirnov} 测试，在局部协调策略下，HV 的硬制动事件（作为潜在的安全影响）的分布发生了显着变化。对于这两种聚类策略，CAV 增加了 HV 的平均换道频率。观察到两种策略之间平均换道频率的盈亏平衡点为 30% MPR，每辆车从 5.42 下降到 5.38。响应 MPR 时，平均换道频率遵循单调增加的模式，在 40% MPR 时每辆车达到最高 5.48。最后，分析了混合动力汽车跟驰模型的交互状态。结果表明，相互作用状态的组成也可能受到 CAV 的影响。