Open AccessResearch on lateral control of autonomous vehicle based on driver steering model
Author(s) -
Runqi Qiu,
Shangfeng Xin
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2206/1/012021
Subject(s) - carsim , model predictive control , control theory (sociology) , path (computing) , computer science , tracking (education) , basis (linear algebra) , control engineering , point (geometry) , linear model , vehicle dynamics , state space , control (management) , simulation , engineering , artificial intelligence , automotive engineering , mathematics , geometry , machine learning , programming language , psychology , pedagogy , statistics
Path tracking is an important issue in autonomous driving research. In this paper, based on the vehicle two-degree-of-freedom linear dynamics model for path tracking, the study of vehicle path tracking is carried out by applying model predictive control. A linear state space model of the vehicle is established based on the linear two-degree-of-freedom dynamics model, which provides the basis for the path tracking research. Based on the established state space model and the model predictive control method, the path tracking control algorithm is established using the preview point of driver steering model instead of the prediction part in the traditional model predictive control algorithm, which reduces the complexity of the algorithm and greatly improves the real-time performance. Finally, the effectiveness of the algorithm is verified by the joint software simulation of CarSim and Simulink.