RETRACTED: The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

Abstract

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

Trajectory tracking of in-wheel motor electric vehicles based on preview time adaptive and torque difference control

“…He et al 5 proposed a trajectory tracking control method based on the deep deterministic strategy gradient algorithm in reinforcement learning for the problem of lateral control, the results show that the method has small lateral deviation and angular deviation in the process of trajectory tracking control, and can meet the tracking requirements under different vehicle speeds. Xu et al 6 used optimal control to plan human-like trajectories in consideration of the natural comfort of passengers to reflect natural driving behavior, thereby improving the acceptability of future unmanned vehicles. Yang et al 7 compared the model predictive control and robust H∞ state feedback control of trajectory tracking under different driving conditions.…”