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Collision Avoidance Path Planning and Tracking Control for Autonomous Vehicles Based on Model Predictive Control.

Ding Dong1, Hongtao Ye1,2, Wenguang Luo1,2

  • 1School of Automation, Guangxi University of Science and Technology, Liuzhou 545036, China.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
Summary
This summary is machine-generated.

Autonomous vehicles can now actively avoid obstacles using a novel model predictive control (MPC) method. This advanced system combines braking and steering for safe collision avoidance, even at high speeds.

Keywords:
active collision avoidanceadaptive cruise controlalternating direction multiplier methodmodel predictive controlpath planningtrajectory tracking

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Area of Science:

  • Robotics
  • Control Systems
  • Automotive Engineering

Background:

  • Autonomous vehicles require advanced systems beyond emergency braking for obstacle avoidance.
  • High-speed scenarios present unique challenges for collision mitigation.

Purpose of the Study:

  • To propose an active collision avoidance method for autonomous vehicles using model predictive control (MPC).
  • To integrate trajectory tracking, adaptive cruise control (ACC), and active steering for comprehensive safety.

Main Methods:

  • Designed an MPC-based trajectory tracking controller using a vehicle dynamics model.
  • Developed MPC-ACC combined control for braking-based collision avoidance.
  • Created active steering for collision avoidance based on a safety distance model.
  • Implemented a nonlinear model predictive control (NMPC) path planning controller.
  • Utilized the alternating direction multiplier method (ADMM) to optimize the solution process.

Main Results:

  • The proposed method effectively achieves collision avoidance through coordinated braking and steering.
  • Demonstrated stability and robustness in high-speed steering maneuvers for obstacle avoidance.
  • Validated performance on the Simulink and CarSim co-simulation platform with static and dynamic obstacles.

Conclusions:

  • The developed algorithm successfully enables autonomous vehicles to avoid obstacles actively.
  • The system ensures the vehicle returns to its intended path post-obstacle avoidance, confirming algorithm effectiveness.