Utilizing vehicle-to-everything (V2X) communication technologies, vehicle platooning systems are expected to realize a new paradigm of cooperative driving with higher levels of traffic safety and efficiency. Connected and Autonomous Vehicles (CAVs) need to have proper awareness of the traffic context. However, as the quantity of interconnected entities grows, the expense of communication will become a significant factor. As a result, the cooperative platoon's performance will be influenced by the communication strategy. While maintaining desired levels of performance, periodic communication can be relaxed to more flexible aperiodic or event-triggered implementations. In this paper, we propose a control-aware communication solution for vehicle platoons. The method uses a fully distributed control-aware communication strategy, attempting to decrease the usage of communication resources while still preserving the desired closed-loop performance characteristics. We then leverage Model-Based Communication (MBC) to improve cooperative vehicle perception in non-ideal communication and propose a solution that combines control-aware communication with MBC for cooperative control of vehicle platoons. Our approach achieves a significant reduction in the average communication rate ($47\%$) while only slightly reducing control performance (e.g., less than $1\%$ speed deviation). Through extensive simulations, we demonstrate the benefits of combined control-aware communication with MBC for cooperative control of vehicle platoons.

翻译：利用车辆对万物（V2X）通信技术，车队系统有望实现更高交通安全与效率的协同驾驶新范式。网联自动驾驶车辆需要具备对交通环境的合理感知能力。然而，随着互联实体数量的增长，通信开销将成为显著影响因素。因此，协同车队的性能将受到通信策略的制约。在保持预期性能水平的同时，周期性通信可被松弛为更灵活的异步或事件触发实现形式。本文提出一种面向车队的通信感知控制方案。该方法采用全分布式通信感知控制策略，旨在降低通信资源消耗的同时维持期望的闭环性能特征。我们进一步利用基于模型的通信技术改善非理想通信条件下的协同车辆感知，并提出了融合通信感知控制与基于模型通信的车队协同控制方案。实验结果表明，本方法在平均通信速率上实现显著降低（47%），同时仅产生轻微的控制性能损失（例如速度偏差低于1%）。通过大量仿真验证，我们证明了通信感知控制与基于模型通信的联合方案对车队协同控制的优越性。