基于动态重排序的城市交叉口互联自动车辆分散最优控制框架
A Decentralized Optimal Control Framework for Connected Automated Vehicles at Urban Intersections with Dynamic Resequencing
摘要：
早期的工作已经建立了一个分散的框架，以最佳地控制连接自动车辆（CAV）通过城市交叉口，而不使用明确的交通信号，同时遵循严格的先进先出（FIFO）排队结构。所提出的解决方案最大限度地减少能源消耗的FIFO为基础的吞吐量最大化的要求。在本文中，我们扩展的解决方案，考虑到不对称的交叉口，通过放松FIFO的约束，并包括一个动态的重新排序过程，以最大限度地提高交通吞吐量。为了研究吞吐量最大化和能量最小化目标之间的权衡，我们利用了几个替代问题的配方。此外，分析了重排序过程的计算复杂性，并证明了其有界性，使得在线实现在计算上是可行的。通过仿真说明了动态重排序过程在吞吐量最大化方面的有效性
英文摘要：
Earlier work has established a decentralized framework to optimally control Connected Automated Vehicles (CAVs) crossing an urban intersection without using explicit traffic signaling while following a strict First-In-First-Out (FIFO) queueing structure. The proposed solution minimizes energy consumption subject to a FIFO-based throughput maximization requirement. In this paper, we extend the solution to account for asymmetric intersections by relaxing the FIFO constraint and including a dynamic resequencing process so as to maximize traffic throughput. To investigate the tradeoff between throughput maximization and energy minimization objectives, we exploit several alternative problem formulations. In addition, the computational complexity of the resequencing process is analyzed and proved to be bounded, which makes the online implementation computationally feasible. The effectiveness of the dynamic resequencing process in terms of throughput maximization is illustrated through simulation
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