Analysis finds improved path planning strategy for autonomous vehicles ensures safe navigation in complex environments, highlighting its control strategy and applicability to unmanned vehicles.
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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Wenjie Wu (2025) studied this question.
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