车辆编队（platooning）作为一种通过多车协同运行提升交通效率、降低能耗及增强道路安全性的潜在技术路径，正受到日益增长的关注。编队控制的关键挑战在于动态操作（如换道）过程中维持稳定且精确的路径跟踪：领航车产生的横向偏差与航向扰动可能向后传播至跟随车辆。因此，鲁棒的纵向与横向控制系统不仅对单车跟踪性能至关重要，也直接影响整个编队的稳定性。为开展实验研究，智能移动与机器人实验室（IMRL）开发了一种用于自主编队研究的缩比多车平台，重点聚焦于协同控制与人在环路（human-in-the-loop）自主性。该平台由一辆人工可操控的领航车和两辆自主跟随车组成，支持对领航-跟随协调机制进行可控且可重复的实验。相较于全尺寸实地测试，该缩比平台提供了更安全、成本更低、灵活性更高的实验环境，适用于快速原型开发、控制器验证及多智能体自主性研究；同时，其物理真实性显著优于纯仿真评估。

Vehicle platooning has attracted increasing attention as a promising approach to improve traffic efficiency, energy consumption, and roadway safety through coordinated multi-vehicle operation. A key challenge in platooning lies in maintaining stable and accurate path tracking during dynamic maneuvers such as lane changes, where lateral deviations and heading disturbances generated by the lead vehicle may propagate downstream to following vehicles. Robust longitudinal and lateral control systems are therefore essential not only for individual vehicle tracking performance, but also for overall platoon stability. For experimental studies, the Intelligent Mobility and Robotics Lab (IMRL) develops a scaled multi-vehicle platform for autonomous platooning research, with a particular emphasis on cooperative control and human-in-the-loop autonomy. This platform consists of one human-operable lead vehicle and two autonomous followers, enabling controlled and repeatable experiments on leader-follower coordination. Compared with full-scale field testing, this scaled platform offers a safer, lower-cost, and more flexible environment for rapid prototyping, controller validation, and multi-agent autonomy studies, while providing stronger physical realism than purely simulation-based evaluations.