The cooperative adaptive cruise control (CACC) algorithm is a simple and effective way to form small-headway platoons so that road capacity and traffic throughput can be improved. The CACC algorithm has been broadly discussed in relation to the highway driving environment where frequent stopping and merging are uncommon. This paper proposes that CACC can also benefit urban arterials, using the appropriate algorithm to predict platoon behavior with optimized trajectories to divide and reform platoons before and after signalized intersections, thus maintaining small, safe headways. Connected vehicle (CV) technology is the key to adapting and improving the CACC algorithm, as it enables the signal phasing plan to be sent to a target CACC platoon and allows vehicles to acquire real-time information from other vehicles in the platoon. In this research, a CV-CACC algorithm is proposed consisting of two functions: platoon division and platoon reforming. The new algorithm is also equipped with acceleration as a new control variable instead of speed, so that the platoon is able to accommodate sharp speed changes around intersections, something the baseline CACC is unable to accommodate. In this study, computer simulations have been conducted to test the reliability of the CV-CACC algorithm and compare its performance against the baseline CACC algorithm.

协同自适应巡航控制（CACC）算法是形成小车距排的一种简单有效的方法，因此可以提高道路通行能力和交通吞吐量。已经针对不经常停车和合并的高速公路驾驶环境对CACC算法进行了广泛的讨论。本文提出，CACC也可以使城市动脉受益，使用适当的算法来预测具有最佳轨迹的行列行为，以在信号交叉口之前和之后对行进行划分和重整，从而保持较小，安全的行进距离。互联汽车（CV）技术是适应和改进CACC算法的关键，因为它使信号调相计划能够发送到目标CACC排，并允许车辆从排中的其他车辆获取实时信息。在这项研究中 提出了一种包含两个功能的CV-CACC算法：排分割和排重整。新算法还配备了加速度作为新的控制变量而不是速度，因此该排能够适应交叉路口附近的急剧速度变化，这是基线CACC无法容纳的。在这项研究中，已经进行了计算机仿真以测试CV-CACC算法的可靠性，并将其性能与基准CACC算法进行比较。