2021
DOI: 10.1177/09544070211009084
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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 cu… Show more

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Cited by 2 publications
(1 citation statement)
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References 37 publications
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“…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.…”
Section: Prefacementioning
confidence: 99%
“…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.…”
Section: Prefacementioning
confidence: 99%