论文标题
部分可观测时空混沌系统的无模型预测
Distributed Dynamic Platoons Control and Junction Crossing Optimization for Mixed Traffic Flows in Smart Cities- Part I. Fundamentals, Theoretical and Automatic Decision Framework
论文作者
论文摘要
本文研究了与智能城市中连接的自动化车辆（CAVS）和社交人类驱动的车辆（HDVS）的混合交通流量的分布式动态排放控制和智能交界处的问题。这本两部分文章的目的是提供一个自动决策框架，以确保安全有效的巡航和跨越连接与多种动态和弹性的排平台骑士，同时与被认为是周围车辆（SVS）的HDV的社交驾驶行为（SDB），以及由Cellular-vehilect-vehile-vehicle-vehicle-dehicle-dehicle-te-dep-x-x Cy-x（C-v2x）（C-v2x）（C-v2x）（c-v2x）（c-v2x）infconction（SVS）（SDB）。我们将表明，尽管智能城市中的混合交通流的非线性，不平滑性和不确定性，但我们提出的自动决策和智能交叉助理系统（ADSCAS）可以解决安全，高效和燃料经济排的解决方案，其中包括四个决策阶段和六个巡游状态在本文中，可以解决。更确切地说，在第一部分中，我们提供了动态的排管理策略，以确定相对于前面的HDV的SDB和即将到来的交通信号灯的排数，在该SDB中，动态排的大小由最小化的安全距离和非线性功能组成。我们还介绍了ADSCA中排的有限状态机器，参考轨迹计划的设计以及燃料经济优化问题的解决方案。
This article studies the problems of distributed dynamic platoons control and smart junction crossing optimization for a mixed traffic flow with connected automated vehicles(CAVs) and social human-driven vehicles(HDVs) in a smart city. The goal of this two-part article is to provide an automatic decision framework to ensure the safe and efficient cruising and crossing junctions with multiple dynamic and resilient platoons CAVs, while against the social driving behaviors(SDBs) of the HDVs considered as surrounding vehicles(SVs) and unknown traffic lights connected by Cellular-Vehicle-to-X (C-V2X) infrastructure. We shall show that despite the nonlinearity, non-smoothness, and uncertainty of mixed traffic flows in smart cities, the solutions of safe, efficient, and fuel economic platoon CAVs control for the above problems can be solved by our proposed automatic decision and smart crossing assistant system(ADSCAS) that includes four decision stages and six cruising states characterized within this article. More precisely, in part I, we provide a dynamic platoon management strategy to determine the platoon size with respect to the SDBs of the preceding HDVs and upcoming traffic lights, where the dynamic platoon size is composed of minimizing safe distances and nonlinear functions of the platoon's cruising velocity. We also present the decision and switching scheme for a finite state machine of platoons in the ADSCAS, the design of the reference trajectory planning, and the solution of the fuel economic optimization problem.
