Application of connected and automated vehicles (CAVs) is expected to have a significant impact on traffic safety and mobility. Although several studies evaluated the effectiveness of CAVs in a small roadway segment, there is a lack of studies analyzing the impact of CAVs in a large-scale network by considering both freeways and arterials. Therefore, the objective of this study is to analyze the effectiveness of CAVs at the network level by utilizing both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. Also, the study proposed a new signal control algorithm through V2I technology to elevate the performance of CAVs at intersections. A car-following model named cooperative adaptive cruise control was utilized to approximate the driving behavior of CAVs in the Aimsun Next microsimulation environment. For the testbed, the research team selected Orlando central business district area in Florida, U.S. To this end, the impacts of CAVs were evaluated based on traffic efficiency (e.g., travel time rate [TTR], speed, and average approach delay, etc.) and safety surrogates (e.g., standard deviation of speed, real-time crash-risk models for freeways and arterials, time exposed time-to-collision). The results showed that the application of CAVs reduced TTR significantly compared with the base condition even with the low market penetration level. Also, the proposed signal control algorithm reduced the approach delay for 94% of the total intersections present in the network. Moreover, safety evaluation results showed a significant improvement of traffic safety in the freeways and arterials under CAV conditions with different market penetration rates.

联网和自动驾驶汽车（CAV）的应用有望对交通安全和机动性产生重大影响。尽管有几项研究评估了CAV在小巷段中的有效性，但仍缺乏通过考虑高速公路和干线来分析CAV在大型网络中的影响的研究。因此，本研究的目的是通过利用车对车（V2V）和车对基础设施（V2I）通信技术来分析CAV在网络级别的有效性。此外，研究还提出了一种通过V2I技术的新信号控制算法，以提高交叉口CAV的性能。利用名为协同自适应巡航控制的跟车模型来近似在Aimsun Next微仿真环境中CAV的驾驶行为。对于测试平台，研究团队选择了美国佛罗里达州奥兰多市中央商务区。为此，基于交通效率（例如，行进时间[TTR]，速度和平均进近延误等）评估了CAV的影响。 ）和安全代理（例如，速度的标准偏差，高速公路和大动脉的实时碰撞风险模型，时间碰撞时间）。结果表明，即使在较低的市场渗透水平下，使用CAV仍比基本情况显着降低了TTR。同样，提出的信号控制算法减少了网络中存在的总路口的94％的进场延迟。此外，安全性评估结果表明，在具有不同市场渗透率的CAV条件下，高速公路和大动脉的交通安全性得到了显着改善。