Physics

Geology

Control engineering

Mobile robot

Pure mathematics

Mathematics

Collision

Engineering

Political science

Artificial intelligence

Control (management)

Programming language

Obstacle

Collision avoidance system

Path (computing)

Potential field

Computer science

Collision avoidance

Field (mathematics)

Computer security

Kinematics

Simulation

Control theory (sociology)

Obstacle avoidance

Classical mechanics

Geophysics

Motion planning

Robot

Energies

Obstacle avoidance systems for autonomous driving vehicles have significant effects on driving safety. The performance of an obstacle avoidance system is affected by the obstacle avoidance path planning approach. To design an obstacle avoidance path planning method, firstly, by analyzing the obstacle avoidance behavior of a human driver, a safety model of obstacle avoidance is constructed. Then, based on the safety model, the artificial potential field method is improved and the repulsive field range of obstacles are rebuilt. Finally, based on the improved artificial potential field, a collision-free path for autonomous driving vehicles is generated. To verify the performance of the proposed algorithm, co-simulation and real vehicle tests are carried out. Results show that the generated path satisfies the constraints of roads, dynamics, and kinematics. The real time performance, effectiveness, and feasibility of the proposed path planning approach for obstacle avoidance scenarios are also verified.

Obstacle Avoidance Path Planning Design for Autonomous Driving Vehicles Based on an Improved Artificial Potential Field Algorithm