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

Institutions

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

Controls
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article

Intelligent Vehicle Trajectory Tracking Based on Horizontal and Vertical Integrated Control

Haimei Liu, Jianfeng Zheng, Jingbo Xu, Jingbo Zhao
2 citations
World Electric Vehicle Journal
Vehicle Dynamics and Control Systems
0.41
article

Intelligent Vehicle Trajectory Tracking Based on Horizontal and Vertical Integrated Control

Haimei Liu, Jianfeng Zheng, Jingbo Xu, Jingbo Zhao
article en
2 citations

Abstract

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.

World Electric Vehicle JournalVol. 15(11)
Shanghai Polytechnic University (CN), Changzhou Institute of Technology (CN), Changzhou University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 39%
Vehicle Dynamics and Control Systems
0.41
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