排
混合自动机
运动规划
控制器(灌溉)
控制理论(社会学)
混合动力系统
车辆动力学
工程类
模型预测控制
控制工程
计算机科学
控制(管理)
汽车工程
人工智能
机器人
机器学习
农学
生物
作者
Zichao Huang,Duanfeng Chu,Chaozhong Wu,Yi He
标识
DOI:10.1109/tits.2018.2841967
摘要
Cooperative driving systems may increase the utilization of road infrastructure resources through coordinated control and platooning of individual vehicles with the potential of enhancing both traffic safety and efficiency. Vehicle cooperative driving is essentially a hybrid system that is a combination of discrete events, i.e., the transition of discrete cooperative maneuvering modes, such as vehicle merging and platoon splitting, as well as continuous vehicle dynamics. In this paper, a novel hybrid system consisting of the discrete cooperative maneuver switch and the continuous vehicle motion control is introduced into a multi-vehicle cooperative control system with a distributed control structure, leading each automated vehicle to conduct path planning and motion control separately. The primary novelty of this paper lies in that it presents a control algorithm combining artificial potential field (APF) approach with model predictive control (MPC), and using the optimizer of the MPC controller to replace the gradient-descending method in the traditional APF approach. Such a method can accomplish both path planning and motion control synchronously. Second, based on hybrid automata, a cooperative maneuver switching model consisting of a system state set and a discrete maneuver transition rule is established for two discrete maneuvers in the cooperative driving system, i.e., single-vehicle cruising and multiple-vehicle platooning. Simulations in several typical traffic scenarios demonstrate the effectiveness of the proposed method.
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