提出一种长时自动驾驶控制方法，提升交通瓶颈处车辆安全与效率。
A Long-Duration Autonomy Approach to Connected and Automated Vehicles
- 基于最优控制构建反应式控制器，融合高阶屏障函数
- 仿真中实现安全通行、高效调度，能耗表现优于传统方法
- 适合智能网联汽车在复杂路口场景应用
本文提出一种面向联网自动驾驶车辆（CAVs）在交通网络中长期运行的自主控制方法，重点关注匝道合流、环岛和交叉口等交通瓶颈场景。基于最优控制原理，设计具备安全、性能与能效保障的反应式控制器。通过高阶控制屏障函数（HOCBFs）保证安全性，并利用时间最优运动基元将其“降阶”为一阶CBFs，以适配实际控制约束。仿真结果表明，该方法在安全性和运行效率方面均优于基于最优控制的传统方案。
原文摘要 · Abstract (English)
In this article, we present a long-duration autonomy approach for the control of connected and automated vehicles (CAVs) operating in a transportation network. In particular, we focus on the performance of CAVs at traffic bottlenecks, including roundabouts, merging roadways, and intersections. We take a principled approach based on optimal control, and derive a reactive controller with guarantees on safety, performance, and energy efficiency. We guarantee safety through high order control barrier functions (HOCBFs), which we ``lift'' to first order CBFs using time-optimal motion primitives. This yields a set of first-order CBFs that are compatible with the control bounds. We demonstrate the performance of our approach in simulation and compare it to an optimal control-based approach.
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