Trajectory Tracking Control Algorithm for Autonomous Vehicle Considering Cornering Characteristics
| Autor: | Xu Zhang, Peng Silun, Chuanxue Song, Feng Xiao, Jingwei Cao, Song Shixin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
General Computer Science Computer science model predictive control Stability (learning theory) 02 engineering and technology CarSim cornering characteristics Vehicle dynamics 020901 industrial engineering & automation Control theory Robustness (computer science) 0202 electrical engineering electronic engineering information engineering General Materials Science MATLAB computer.programming_language autonomous vehicle 020208 electrical & electronic engineering General Engineering trajectory tracking control Model predictive control Trajectory Driving assistance lcsh:Electrical engineering. Electronics. Nuclear engineering computer lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 8, Pp 59470-59484 (2020) |
| ISSN: | 2169-3536 |
| Popis: | Trajectory tracking control is a key technology in the research and development of autonomous vehicles. With the aim of addressing problems such as low control accuracy and poor real-time performance, which can occur easily when an autonomous vehicle avoids obstacles, this research focuses on the trajectory tracking control algorithm for autonomous vehicle considering cornering characteristics. First, the vehicle dynamics model and tire model are established through appropriate simplification. Then, based on the basic principle of model predictive control, a linear time-varying model predictive controller (LTV MPC) that considers the cornering characteristics is designed and optimized. Finally, using CarSim and MATLAB/Simulink software, a joint simulation model is established and the trajectory tracking performance of the controlled vehicle under different vehicle speeds and road adhesion conditions are tested through simulation experiments in combination with the double-shift line reference trajectory. The simulation results show the LTV MPC controller that considers cornering characteristics has good self-adaptability under complicated and severe working conditions, and no cases, such as car sideslip or track departure, were observed. Compared with other controllers and algorithms, the designed trajectory tracking controller has remarkable comprehensive performance, exhibits superior robustness and anti-interference ability, and significant improvements in the trajectory tracking control accuracy and real-time performance. The proposed control algorithm is of great importance in improving the tracking stability and driving safety of autonomous vehicles under complex extreme conditions and conducive to the further development and improvement of the technological level of intelligent vehicle driving assistance. |
| Databáze: | OpenAIRE |
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