论文标题
多种交通情况的连接和自动化车辆的最佳协调
Decentralized Optimal Coordination of Connected and Automated Vehicles for Multiple Traffic Scenarios
论文作者
论文摘要
连接和自动化的车辆（CAVS）为优化能源消耗和旅行时间提供了最有趣的机会。文献中已经提出了几种方法，使骑士可以在存在潜在冲突的情况下进行协调，例如，在信号交叉点，在道路和回旋处合并，减少能源消耗并优化交通流量。在本文中，我们考虑了由多种交通情况组成的走廊中协调骑士的问题。我们制定了一个两级优化问题，在该问题中，我们最大程度地提高了高层问题中的流量吞吐量，并得出了封闭形式的分析解决方案，该解决方案在低级问题中，在燃油消耗方面，为每个CAV提供了最佳控制输入。我们通过在100％CAV培训速率下模拟来验证溶液的有效性。与由人类驱动的车辆组成的基线情况相比，车辆的燃油消耗和旅行时间大大减少。
Connected and automated vehicles (CAVs) provide the most intriguing opportunity to optimize energy consumption and travel time. Several approaches have been proposed in the literature that allow CAVs to coordinate in situations where there is a potential conflict, for example, in signalized intersections, merging at roadways and roundabouts, to reduce energy consumption and optimize traffic flow. In this paper, we consider the problem of coordinating CAVs in a corridor consisting of multiple traffic scenarios. We formulate a two-level optimization problem in which we maximize traffic throughput in the upper-level problem, and derive a closed-form analytical solution that yields the optimal control input for each CAV, in terms of fuel consumption, in the low-level problem. We validate the effectiveness of the solution through simulation under 100% CAVpenetration rate. Fuel consumption and travel time for the vehicles are significantly reduced compared to a baseline scenario consisting of human-driven vehicles.
