论文标题
在混合交通交叉点上连接的自动化车辆的安全性和数据驱动的预测控制
Safety-Aware and Data-Driven Predictive Control for Connected Automated Vehicles at a Mixed Traffic Signalized Intersection
论文作者
论文摘要
典型的城市信号交叉点在由连接的自动化车辆（CAVS）和人类驱动的车辆（HDV）组成的混合交通环境中提出了重大的建模和控制挑战。在本文中，我们解决了在混合交通环境中为CAV提供安全轨迹的问题，该问题优先考虑后端碰撞避免时，当前面的HDV接近交叉路口的黄色和红色信号阶段。我们提出了一个预测性控制框架，该框架采用递归最小二乘算法实时近似于前面的HDV的驾驶行为，然后使用此近似值来在有限的地平线中得出安全感知的轨迹。我们通过数值模拟来验证我们提出的框架的有效性，并分析控制框架的鲁棒性。
A typical urban signalized intersection poses significant modeling and control challenges in a mixed traffic environment consisting of connected automated vehicles (CAVs) and human-driven vehicles (HDVs). In this paper, we address the problem of deriving safe trajectories for CAVs in a mixed traffic environment that prioritizes rear-end collision avoidance when the preceding HDVs approach the yellow and red signal phases of the intersection. We present a predictive control framework that employs a recursive least squares algorithm to approximate in real time the driving behavior of the preceding HDVs and then uses this approximation to derive safety-aware trajectory in a finite horizon. We validate the effectiveness of our proposed framework through numerical simulation and analyze the robustness of the control framework.
