Improved Artificial Potential Field and Model Predictive Control for Autonomous Vehicle Local Path Planning

Wenjie Wu

doi:10.54097/mthe3634

Authors

Wenjie Wu

DOI:

https://doi.org/10.54097/mthe3634

Keywords:

Autonomous vehicle, Path planning, Model predictive control, Artificial potential field method

Abstract

In this paper, a local path planning algorithm based on improved artificial potential field (APF) method and model predictive control (MPC) is proposed for the safe driving of autonomous vehicles under complex working conditions. An adjustment factor is introduced to establish a novel obstacle repulsive potential field and an enhanced gravitational potential field, which are then integrated with the MPC algorithm. Secondly, introduce the potential field at the road boundary to ensure that vehicles travel within the safe area of the road. Finally, simulation results demonstrate the effectiveness of the proposed control strategy in ensuring the safe navigation of unmanned vehicles in complex operational environments. Compared with the traditional MPC path planning strategy, this strategy can combine the actual road condition information to establish a more accurate road environment model and finally plan a safe local expected trajectory.

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