Platoon formation with connected and automated vehicles (CAVs) in a mixed traffic environment poses significant challenges due to the presence of human-driven vehicles (HDVs) with unknown dynamics and control actions. In this paper, we develop a safety-prioritized receding horizon control framework for creating platoons of HDVs preceded by a CAV Our framework ensures indirect control of the following HDVs by directly controlling the leading CAV given the safety constraints. The framework utilizes a data-driven prediction model that is based on the recursive least squares algorithm and the constant time headway relative velocity car-following model to predict future trajectories of human-driven vehicles. To demonstrate the efficacy of the proposed framework, we conduct numerical simulations and provide the associated scalability, robustness, and performance analyses.

由于存在具有未知动力学和控制动作的人力驾驶车辆 (HDV)，因此在混合交通环境中使用联网和自动驾驶车辆 (CAV) 编队构成了重大挑战。在本文中，我们开发了一个安全优先的后退地平线控制框架，用于创建前面有 CAV 的 HDV 排。我们的框架通过在给定安全约束的情况下直接控制领先的 CAV 来确保对后续 HDV 的间接控制。该框架利用基于递归最小二乘算法和恒定时间车头时距相对速度跟车模型的数据驱动预测模型来预测人类驾驶车辆的未来轨迹。为了证明所提出框架的有效性，我们进行了数值模拟并提供了相关的可扩展性、稳健性、