标题： 信号交叉口交通密度减少的自动驾驶车辆协同控制：一种MPC方法 显示英文标题

标题： Coordinated Control of Autonomous Vehicles for Traffic Density Reduction at a Signalized Junction: An MPC Approach

摘要： 有效且安全的交通管理由于城市交通系统的快速发展而成为一个关键问题。 联网自动驾驶车辆（CAVs）具备相互连接和与相邻基础设施连接的能力，为提高交通流和协调性提供了新的机遇。 本工作提出了一种双模式模型预测控制（MPC）架构，解决两个相互关联的问题：减轻信号交叉口的交通密度以及在高密度交通条件下实现无缝协作的变道。 本工作的目标是为CAVs提供响应式的决策，从而提高城市出行的效率和安全性。 此外，通过集成在线计算的最大控制不变终端集，我们确保了所提出的MPC方案的递归可行性和收敛性。 最后，通过数值仿真验证了所提出方法的有效性。 显示英文摘要

摘要： The effective and safe management of traffic is a key issue due to the rapid advancement of the urban transportation system. Connected autonomous vehicles (CAVs) possess the capability to connect with each other and adjacent infrastructure, presenting novel opportunities for enhancing traffic flow and coordination. This work proposes a dual-mode model predictive control (MPC) architecture that tackles two interrelated issues: mitigating traffic density at signalized junctions and facilitating seamless, cooperative lane changes in high-density traffic conditions. The objective of this work is to facilitate responsive decision-making for CAVs, thereby enhancing the efficiency and safety of urban mobility. Moreover, we ensure recursive feasibility and convergence of the proposed MPC scheme by the integration of an online-calculated maximal control invariant terminal set. Finally, the efficacy of the proposed approach is validated through numerical simulation.