Trajectory tracking of four-wheel driving and steering autonomous vehicle under extreme obstacle avoidance condition

Abstract

In the condition of actual obstacle avoidance, where longitudinal deceleration is large and variable, it is difficult for the autonomous vehicle to simultaneously track longitudinal velocity and lateral motion. In addition, when the planned trajectory exceeds the adhesion of the road, the vehicle is also prone to losing stability. Most studies of the obstacle avoidance process only consider constant velocity. This paper presents a novel control architecture for four-wheel driving (4WD) and four-wheel steering (4WS) autonomous vehicles to track predefined trajectory and velocity. It is proposed to use preview technology to obtain the desired state of the vehicle and a controller based on multi-input multi-output nonlinear model predictive control (MIMO-NMPC) that considers the deceleration-steering combination condition. According to the sensitivity analysis of the influence of tyre slip rate on tyre lateral force, the optimal working boundary of the tyre is determined. The output of the controller is constrained by estimating tyre force to prevent tyre force saturation and maximise tyre adhesion limit utilisation. The simulation results demonstrate that the proposed controller can better track the trajectory and longitudinal velocity with a faster response on the high-adhesion road. The overshoot of lateral displacement and the maximum error of longitudinal velocity are less than 0.03m and 0.2m/s, respectively. In addition, when the planned trajectory exceeds the adhesion limit of the road, it can still follow the desired trajectory as closely as possible while maintaining stability on low-adhesion roads.