论文标题
在混合交通环境中，排队形成的安全优先置换的水平控制框架
A Safety-Prioritized Receding Horizon Control Framework for Platoon Formation in a Mixed Traffic Environment
论文作者
论文摘要
混合交通环境中与连接和自动化车辆（CAV）的排组构成了巨大的挑战，这是由于存在人类驱动的车辆（HDV），并具有未知的动态和控制动作。在本文中，我们开发了一个安全优先级的后退控制框架，用于创建在CAV之前的HDVS的排。我们的框架可以通过直接控制领先的CAV，从而确保对以下HDV的间接控制。该框架利用数据驱动的预测模型，该模型基于递归最小二乘算法和恒定时间前进的相对速度速度遵循模型来预测人类驱动车辆的未来轨迹。为了证明所提出的框架的功效，我们进行数值模拟并提供相关的可扩展性，鲁棒性和性能分析。
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.
