Model predictive control of connected vehicles under automated driving at path-free signal-free intersections

Elham Ahmadi, Rodrigo Castelan Carlson
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Abstract

In this paper, we tackle the problem of real-time multi-vehicle interactions at signalfree and path-free intersections, which we call plazas, aiming for an efficient use of the intersection space. We propose a method that combines the path planning and path following tasks of connected vehicles under automated driving in one formulation. The method extends the standard nonlinear model predictive contouring control for application at intersections via the generation of multiple timeindependent reference paths. The goal is to maximize the progress of each vehicle along its reference path and penalize the rate of the control inputs while handling the continuous arrivals of the vehicles. The method is demonstrated using numerical simulation of vehicles at an intersection. The simulation results show that the proposed method achieves optimal and safe trajectories of the vehicles with driving flexibility and the possibility of better utilizing the intersection space.
无信号灯交叉路口自动驾驶下联网车辆的模型预测控制
在本文中,我们解决了无标志和无路径交叉路口(我们称之为广场)的多车实时交互问题,旨在有效利用交叉路口空间。我们提出了一种方法,将自动驾驶下联网车辆的路径规划和路径跟随任务结合在一个表述中。该方法通过生成多个与时间无关的参考路径,将标准非线性模型预测轮廓控制扩展到交叉路口应用。目标是在处理车辆连续到达的同时,最大化每辆车沿其参考路径的前进速度,并对控制输入的速率进行惩罚。该方法通过对十字路口车辆的数值模拟进行了演示。仿真结果表明,所提出的方法实现了车辆的最佳安全轨迹,同时具有驾驶灵活性和更好地利用交叉路口空间的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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