论文标题
具有事件/自触发控制屏障功能的连接自动化车辆的最佳控制
Optimal Control of Connected Automated Vehicles with Event/Self-Triggered Control Barrier Functions
论文作者
论文摘要
我们解决了控制交通网络冲突区域中受到严格安全限制的冲突区域中连接和自动化车辆（CAV）的问题。已经表明，可以通过可拖动的最佳控制问题制剂和使用控制屏障功能（CBF）的结合来解决此类问题，以保证所有约束满意。可以将这些解决方案简化为一系列二次程序（QP），这些序列可以在离散的时间步骤上有效地在线解决。但是，每个这样的QP的可行性不能在每个时间步骤中保证。为了克服这一限制，我们既开发了事件触发的方法，又开发了一种自触发的方法，以便下一个QP由正确定义的事件触发。我们表明，两种方法都以不同的方式消除了由于时间驱动的间采样效果而消除了不可行的情况，从而消除了选择时间步长大小的需求。包括模拟示例以比较这两个新方案，并说明如何显着降低整体不可或缺的能力，同时减少骑士之间在不损害性能的情况下进行交流的需求。
We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints. It has been shown that such problems can be solved through a combination of tractable optimal control problem formulations and the use of Control Barrier Functions (CBFs) that guarantee the satisfaction of all constraints. These solutions can be reduced to a sequence of Quadratic Programs (QPs) which are efficiently solved on-line over discrete time steps. However, the feasibility of each such QP cannot be guaranteed over every time step. To overcome this limitation, we develop both an event-triggered approach and a self-triggered approach such that the next QP is triggered by properly defined events. We show that both approaches, each in a different way, eliminate infeasible cases due to time-driven inter-sampling effects, thus also eliminating the need for selecting the size of time steps. Simulation examples are included to compare the two new schemes and to illustrate how overall infeasibilities can be significantly reduced while at the same time reducing the need for communication among CAVs without compromising performance.
