卡西姆
运动规划
模型预测控制
控制器(灌溉)
机器人学
控制工程
工程类
方案(数学)
路径(计算)
运动控制
过程(计算)
自适应控制
控制理论(社会学)
运动控制器
控制(管理)
机器人
人工智能
车辆动力学
计算机科学
汽车工程
操作系统
数学分析
生物
程序设计语言
数学
农学
作者
Yixiao Liang,Yinong Li,Amir Khajepour,Yanjun Huang,Yechen Qin,Ling Zheng
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-02-12
卷期号:23 (9): 16083-16097
被引量:26
标识
DOI:10.1109/tits.2022.3147972
摘要
In the research of autonomous vehicles, most existing studies treat the decision/planning and control as two separate problems. This idea originates from robotics. But since there are essential differences between robot and autonomous vehicle, the structure in Robotics may not be suitable for autonomous vehicles. Considering decision/planning and control separately may affect the performance of autonomous vehicle under complex driving conditions. To fill in the research gap, this paper proposes a novel scheme which considers the local motion planning and control in a combined manner. Firstly, the local motion planning is transformed into the longitudinal control problem based on the proposed scenario adaptive MPC, by which the motion behavior (driving along the global path, car-following, lane-change) can be automatically decided. Then, the lateral MPC controller is designed to track the global path and conduct the local motion commands. To ensure the performance of the path tracking control and a smooth lane-change process simultaneously, an adaptive weight mechanism is introduced in the lateral controller. Comprehensive case studies including both straight and curve road are conducted based on Carsim-Simulink co-simulation platform. The results show that the proposed algorithm can not only ensure the vehicle safety in complex driving conditions, but also ensure that the vehicle can drive at its desired velocity as much as possible by intelligently judging the most proper motion behaviors.
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