| PATH PLANNING AND PATH TRACKING FOR AUTONOMOUS VEHICLE BASED ON MPC WITH ADAPTIVE DUAL-HORIZON-PARAMETERS
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| Yaohua Li , Jikang Fan , Yang Liu , Xiaoyu Wang |
| Chang’an University |
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| ABSTRACT |
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According to the position relationship between the vehicle and the obstacle, a new obstacle avoidance path
planner was designed to solve the limitation of traditional local obstacle avoidance path planner in excessive obstacle avoidance.
In order to improve the control accuracy of the path tracking controller and ensure the stability of the vehicle, a comprehensive
evaluation index of path tracking performance considering control accuracy and driving stability was established. The optimal
prediction time domain and control time domain parameters at different vehicle speeds were obtained, and an adaptive dual
time domain parameter path tracking controller was designed. Based on the joint-simulation platform, the integrated structure
of the planning layer and the control layer was simulated and verified. Simulation results show that the new obstacle avoidance
function can avoid excessive obstacle avoidance while ensuring real-time performance, and improve the driving stability of the
vehicle. The adaptive time-domain parameter path tracking controller has better comprehensive control performance and can
improve driving safety under extreme conditions. The integrated structure of local obstacle avoidance path planning and path
tracking control are beneficial for the vehicle to plan and accurately track the local obstacle avoidance path in multiple static
obstacle scenes. |
| Key Words:
Autonomous vehicles, Model predictive control, Obstacle avoidance, Local path planning, Path tracking
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Corresponding Author.
Yaohua Li , Email. 
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