Intelligent Vehicle Trajectory Tracking Based on Horizontal and Vertical Integrated Control
To address the common issues of accuracy and stability in trajectory tracking tasks for autonomous vehicles, this study proposes an innovative composite control strategy that skillfully integrates lateral and longitudinal dynamic control. For lateral control, model predictive control (MPC) theory is introduced to compute the front wheel steering angle that ensures optimal trajectory following. On the longitudinal control level, the vehicle’s acceleration and deceleration logic are finely tuned to ensure precise adherence to the preset speed trajectory. More importantly, by deeply integrating these two control methods, the comprehensive coordination of the vehicle’s lateral and longitudinal movements is achieved. To validate the effectiveness of the proposed control strategy, simulations were conducted using the CarSim and MATLAB/Simulink platforms. The analysis of the simulation results confirms that the proposed method effectively improves speed tracking stability and significantly enhances path tracking accuracy and overall driving stability.
Authors
- Haimei Liu (ORCID: https://orcid.org/0000-0003-0322-3499)
- Jianfeng Zheng (ORCID: https://orcid.org/0000-0001-9200-863X)
- Jingbo Xu
- Jingbo Zhao
Institutions
- Shanghai Polytechnic University (CN)
- Changzhou Institute of Technology (CN)
- Changzhou University (CN)
Publication Details
- Journal
- World Electric Vehicle Journal
- Published
- 2024-11-07
- DOI
- https://doi.org/10.3390/wevj15110513
- Citations
- 2
- Primary Topic
- Vehicle Dynamics and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.41
Funders
- National Natural Science Foundation of China