Integrated trajectory planning and control for obstacle avoidance manoeuvre using non‐linear vehicle MP algorithm

Abstract

In the current literature, model-predictive (MP) algorithm is widely applied in autonomous vehicle trajectory planning and control but most of current studies only apply the linear tyre model which cannot accurately present the tyre non-linear characteristic. Furthermore, most of these studies separately consider the trajectory planning and trajectory control of autonomous vehicle and few of them have integrated the trajectory planning and trajectory control together. To fill in above research gaps, this study proposes the integrated trajectory planning and trajectory control method using nonlinear vehicle MP algorithm. In order to fully utilise the advantages of four-wheel-independent-steering (4WIS) and fourwheel-independent-driving (4WID) vehicle, the MP algorithm is proposed based on four wheel dynamics model and nonlinear Dugoff tyre model. This study also proposes the mathematic modelling of the static obstacle and dynamic obstacle for the obstacle avoidance manoeuvre of the autonomous vehicle. Finally, simulation results have been presented to show the effectiveness of proposed control method.

Echo State Network for Extended State Observer and Sliding Mode Control of Vehicle Drive Motor with Unknown Hysteresis Nonlinearity

“…And in literature [7], the autonomous vehicles were researched with extended Kalman filter designing minimum model error tracking control that considers the input saturation in real vehicle systems that always contains the issue of the input saturation. Compared with many other literatures that utilized linear tyre model, Li et al [8] had investigated the nonlinear tyre model with vehicle MP algorithm. Sun et al [9,10] investigated the variable stiffness and damping model of magnetorheological (MR) vehicle suspension system.…”