论文标题
连接和自动化车辆的多车道合并中分散的最佳控制
Decentralized Optimal Control in Multi-lane Merging for Connected and Automated Vehicles
论文作者
论文摘要
我们解决了从两条多车道道路到达的最佳控制连接和自动化车辆（CAV）的问题，并在多个点合并，目的是将每个CAV的旅行时间和能源消耗最小化，并受到速度依赖性安全性限制，以及速度和加速约束。在两条单车道的先前工作中解决了这个问题。多车道道路的直接扩展受到获得明确最佳控制解决方案所需的计算复杂性的限制。取而代之的是，我们提出了一个通用框架，该框架将多车道合并问题转换为每个CAV的分散的最佳控制问题，以较不保守的方式。为此，我们采用联合最佳控制和屏障功能方法来有效地为每个CAV获得最佳控制，并保证满足所有约束。包括模拟示例，以将提议的框架的性能与人类驱动车辆提供的基线进行比较，结果显示时间和能量指标的显着改善。
We address the problem of optimally controlling Connected and Automated Vehicles (CAVs) arriving from two multi-lane roads and merging at multiple points where the objective is to jointly minimize the travel time and energy consumption of each CAV subject to speed-dependent safety constraints, as well as speed and acceleration constraints. This problem was solved in prior work for two single-lane roads. A direct extension to multi-lane roads is limited by the computational complexity required to obtain an explicit optimal control solution. Instead, we propose a general framework that converts a multi-lane merging problem into a decentralized optimal control problem for each CAV in a less-conservative way. To accomplish this, we employ a joint optimal control and barrier function method to efficiently get an optimal control for each CAV with guaranteed satisfaction of all constraints. Simulation examples are included to compare the performance of the proposed framework to a baseline provided by human-driven vehicles with results showing significant improvements in both time and energy metrics.
