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Overtaking Trajectory Planning Based on Model Predictive Control

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Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13457))

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Abstract

Autonomous driving technology can greatly increase road safety and reduce accidents, and has become a hot research topic in academia and industry today. However, traditional vehicle motion planning methods often have difficulty in balancing real-time performance with trajectory quality. This paper designs a trajectory planning method based on model predictive control technology, which transforms the motion planning problem into a quadratic planning problem. Compared with previous methods, the proposed method can generate trajectories that meet the requirements of vehicle kinematics and satisfy the requirements of comfort and energy saving while ensuring obstacle avoidance and real-time, and verifies the feasibility of this method in simulation experiments.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant U1813224, Grant 62173113, in part by the Science and Technology Innovation Committee of Shenzhen Municipality under Grant GXWD20201230155427003-20200821173613001 and Grant JCYJ20200109113412326.

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Authors and Affiliations

  1. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

    Zihan Yuan & Jun Xu

  2. Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai, China

    Jun Xu

Authors
  1. Zihan Yuan
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  2. Jun Xu
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Corresponding author

Correspondence to Jun Xu .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Honghai Liu

  2. Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

  3. Shenyang Institute of Automation, Shenyang, Liaoning, China

    Lianqing Liu

  4. Harbin Institute of Technology, Harbin, China

    Li Jiang

  5. Shanghai Jiao Tong University, Shanghai, China

    Guoying Gu

  6. Shenzhen Institutes of Advanced Technology, Shenzhen, China

    Xinyu Wu

  7. Harbin Institute of Technology, Harbin, China

    Weihong Ren

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Yuan, Z., Xu, J. (2022). Overtaking Trajectory Planning Based on Model Predictive Control. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13457. Springer, Cham. https://doi.org/10.1007/978-3-031-13835-5_50

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  • DOI: https://doi.org/10.1007/978-3-031-13835-5_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13834-8

  • Online ISBN: 978-3-031-13835-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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