【SCI】Dynamic Trajectory Planning and Tracking for Autonomous Vehicle With Obstacle Avoidance Based on Model Predictive Control

Release time:2022-03-30  Hits:

• Affiliation of Author(s):机电工程学院
• Journal:IEEE Access
• Funded by:国家自然科学基金项目
• Key Words:Autonomous vehicle, dynamic obstacles, moving trend function, dynamic planning and tracking, single-level controller.
• Abstract:In this study, an obstacle avoidance controller based on nonlinear model predictive control is designed in autonomous vehicle navigation. The reference trajectory is predened using a sigmoid function in accordance with road conditions. When obstacles suddenly appear on a predened trajectory, the reference trajectory should be adjusted dynamically. For dynamic obstacles, a moving trend function is constructed to predict the obstacle position variances in the predictive horizon. Furthermore, a risk index is constructed and introduced into the cost function to realize collision avoidance by combining the relative position relationship between vehicle and obstacles in the predictive horizon. Meanwhile, lateral acceleration constraint is also considered to ensure vehicle stability. Finally, trajectory dynamic planning and tracking are integrated into a single-level model predictive controller. Simulation tests reveal that the designed controller can ensure real-time trajectory tracking and collision avoidance.
• Co-author:zhangniaona,张邦成
• First Author:lishaosong
• Indexed by:Journal paper
• Volume:7
• Page Number:2
• Translation or Not:no
• Date of Publication:2019-09-12