论文标题
在多个相邻交叉点上对连接和自动化车辆的最佳控制
Optimal Control of Connected and Automated Vehicles at Multiple Adjacent Intersections
论文作者
论文摘要
在本文中，我们为连接和自动化的车辆（CAVS）建立了一个分散的最佳控制框架，该框架（CAVS）越过多个相邻的，多车道的无信号交叉点，以最大程度地减少能源消耗并改善交通吞吐量。我们的框架由两层计划组成。在高层规划中，每个CAV与最佳车道一起在每个交叉路口递归地计算其最佳到达时间，以改善交通吞吐量。在低级计划中，我们制定了一个具有内点约束的能量最佳控制问题，其解决方案可以在每个CAV的最佳控制输入（加速/减速）中，以在上层计划指定的时间时跨越交叉点。此外，我们将提出的双层框架的结果扩展到跟踪CAVS的最佳位置时包含有界稳态误差。最后，我们通过模拟对称和非对称交集以及与传统信号交集的比较来证明所提出的框架的有效性。
In this paper, we establish a decentralized optimal control framework for connected and automated vehicles (CAVs) crossing multiple adjacent, multi-lane signal-free intersections to minimize energy consumption and improve traffic throughput. Our framework consists of two layers of planning. In the upper-level planning, each CAV computes its optimal arrival time at each intersection recursively along with the optimal lane to improve the traffic throughput. In the low-level planning, we formulate an energy-optimal control problem with interior-point constraints, the solution of which yields the optimal control input (acceleration/deceleration) of each CAV to cross the intersections at the time specified by the upper-level planning. Moreover, we extend the results of the proposed bi-level framework to include a bounded steady-state error in tracking the optimal position of the CAVs. Finally, we demonstrate the effectiveness of the proposed framework through simulation for symmetric and asymmetric intersections and comparison with traditional signalized intersections.
