@inproceedings{eb527026356041dfbb7c4b1275c38e3f,
title = "A Path Planning and Tracking Control for Autonomous Vehicle with Obstacle Avoidance",
abstract = "This paper presents a path planning and tracking framework to implement obstacle avoidance for autonomous car. The safe driving area model, which is made up of a serious of nodes, designed by using the longitudinal and lateral motion relationship of the vehicle, is proposed to describe the location of automobile with sideslip constraint in driving and position of the obstacles on the road, and Q-learning algorithm is used to learn the optimal strategy on each node and the optimal path is obtained under the predefined rules. In order to execute precise path tracking control, linear output regulation method is introduced to design the tracking controller based on both the kinematic and dynamic vehicle models. CarSim simulations are conducted with different scenarios and the effectiveness of the proposed framework is demonstrated.",
keywords = "Autonomous vehicle, obstacle avoidance, tracking control",
author = "Xin Wang and Xinghu Yu and Weichao Sun",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Chinese Automation Congress, CAC 2020 ; Conference date: 06-11-2020 Through 08-11-2020",
year = "2020",
month = nov,
day = "6",
doi = "10.1109/CAC51589.2020.9327065",
language = "英语",
series = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2973--2978",
booktitle = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
address = "美国",
}