The obstacle avoidance assistance control of multi-axle distributed heavy vehicles

Based on the artificial potential field theory, a hierarchical obstacle avoidance assisted driving framework is proposed in this paper, in order to solve the obstacle avoidance assisted driving problem of distributed heavy vehicles. Initially, a desired lateral position potential field (DLPPF) that reflects the driver’s driving intention is applied based on the constant turn rate and velocity (CTRV) model. And a real-time obstacle avoidance path can be obtained and further updated through a comprehensive consideration of the safety of obstacle avoidance and the obstacle repulsion potential field (ORPF). In addition, a differential drive assistance steering (DDAS) on the heavy vehicle steering bridge has been adopted to realize avoiding obstacles, and additional yaw moment to the vehicle’s non-steering axle has been utilized to ensure the maneuverability and stability of vehicle. Aiming to solve the lower layer control problem, a variable weight controller based on model predictive control (MPC) is designed to coordinate path tracking performance and dynamics control. Finally, through simulations and comparisons, the effectiveness of the obstacle avoidance strategy is verified.