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Research on Human Driving Characterised Trajectory Planning and Trajectory Tracking Control Based on a Test Track

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Abstract

The trajectory planning plays an important role in realizing the autonomous driving process. The trajectory that reflects the driving habits of human drivers and conforms with people’s driving intuition enables a vehicle to operate smoother and more comfortable when passing through corners, which could improve the acceptability of autonomous vehicles in the market in the future. The research of this paper focuses on planning a human driving characterised trajectory along a road based on the test track that could reflect natural driving behaviour in corners considering the sense of natural and comfortable for the occupants. Firstly, the data collected of the test track are processed and the coordinate system transformation is completed, and the human tested trajectories in the test track is extracted and analysed. Then, the human driving characterised trajectory planning is completed based on optimal control in a lane section on the test track. The trajectory tracking control algorithm based on LQR is designed, and a CarSim/Simulink co-simulation platform is established to track the optimal trajectory generated in a lane and the lane centreline trajectory to verify the superiority of the planned trajectory. The results show that compared with the centreline trajectory, the human driving characterised trajectory planned enables the autonomous vehicle operates smoother and more comfortable, and reflects the characteristic of human drivers to a large extent.

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Author information

Authors and Affiliations

  1. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, China

    Xing Xu, Xinwei Jiang, Ju Xie & Feng Wang

  2. Pan Asia Technical Automotive Center, Shanghai, 201206, China

    Minglei Li

Authors
  1. Xing Xu
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  2. Xinwei Jiang
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  3. Ju Xie
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  4. Feng Wang
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  5. Minglei Li
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Corresponding authors

Correspondence to Xing Xu or Ju Xie.

Additional information

Xing Xu received his B.Sc. degree in vehicle engineering, an M.Sc. degree in control theory and control engineering, and a Ph.D. degree in agricultural electrification and automation from Jiangsu University, Zhenjiang, China, in 2002, 2006, and 2010, respectively. He is currently a Professor with the Automotive Engineering Research Institute, Jiangsu University. His research interests include modeling, optimization, fault diagnosis, and control of vehicle dynamic systems.

Xinwei Jiang received his B.Sc. and M.Sc. degrees in vehicle engineering from Jiangsu University, Zhenjiang, China, in 2016 and 2019, respectively. He is currently a Ph.D. candidate with the Automotive Engineering Research Institute, Jiangsu University. His research interests include autonomous driving technology and automotive electronic control.

Ju Xie received his B.Sc. and M.Sc. degrees in vehicle engineering from Jiangsu University, Zhenjiang, China, in 2015 and 2018, respectively. He is currently a Ph.D. candidate with the Automotive Engineering Research Institute, Jiangsu University. His research interests include vehicle dynamics and control, driver behavior modeling, and intelligent control for autonomous vehicles.

Feng Wang received his B.Sc. and Ph.D. degrees from Northwestern Polytechnical University, Xi’an, China, in 2008 and 2014, respectively. He is currently an Associate Professor with the Automotive Engineering Research Institute, Jiangsu University. His research interests include analysis and control of complex electromechanical coupling transmission system and matching, and optimization and coordinated control of hybrid multi-power source coupling transmission system.

Minglei Li received his B.Sc. and M.Sc. degrees in vehicle engineering from Jiangsu University, Zhenjiang, China, in 2018 and 2021, respectively. He is currently an engineer with the Pan Asia Technical Automotive Center. His research interests include autonomous driving technology and automotive path-following control.

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This work was supported by the Primary Research & Development Plan of Jiangsu Province (No. BE2019010) and the the National Natural Science Foundation of China (No. U20A20331).

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Xu, X., Jiang, X., Xie, J. et al. Research on Human Driving Characterised Trajectory Planning and Trajectory Tracking Control Based on a Test Track. Int. J. Control Autom. Syst. 21, 1258–1272 (2023). https://doi.org/10.1007/s12555-021-0785-6

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  • DOI: https://doi.org/10.1007/s12555-021-0785-6

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