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Design of a Path-Tracking Steering Controller for Autonomous Vehicles

Author

Listed:
  • Chuanyang Sun

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Xin Zhang

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Lihe Xi

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Ying Tian

    (Beijing Jiaotong University Yangtze River Delta Research Institute, Zhenjiang 212009, China)

Abstract

This paper presents a linearization method for the vehicle and tire models under the model predictive control (MPC) scheme, and proposes a linear model-based MPC path-tracking steering controller for autonomous vehicles. The steering controller is designed to minimize lateral path-tracking deviation at high speeds. The vehicle model is linearized by a sequence of supposed steering angles, which are obtained by assuming the vehicle can reach the desired path at the end of the MPC prediction horizon and stay in a steady-state condition. The lateral force of the front tire is directly used as the control input of the model, and the rear tire’s lateral force is linearized by an equivalent cornering stiffness. The course-direction deviation, which is the angle between the velocity vector and the path heading, is chosen as a control reference state. The linearization model is validated through the simulation, and the results show high prediction accuracy even in regions of large steering angle. This steering controller is tested through simulations on the CarSim-Simulink platform (R2013b, MathWorks, Natick, MA, USA), showing the improved performance of the present controller at high speeds.

Suggested Citation

  • Chuanyang Sun & Xin Zhang & Lihe Xi & Ying Tian, 2018. "Design of a Path-Tracking Steering Controller for Autonomous Vehicles," Energies, MDPI, vol. 11(6), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1451-:d:150611
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    References listed on IDEAS

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    1. Aijuan Li & Wanzhong Zhao & Xibo Wang & Xuyun Qiu, 2018. "ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle’s Active Obstacle Avoidance System," Energies, MDPI, vol. 11(1), pages 1-21, January.
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    Cited by:

    1. Leon Prochowski & Mateusz Ziubiński & Patryk Szwajkowski & Mirosław Gidlewski & Tomasz Pusty & Tomasz Lech Stańczyk, 2021. "Impact of Control System Model Parameters on the Obstacle Avoidance by an Autonomous Car-Trailer Unit: Research Results," Energies, MDPI, vol. 14(10), pages 1-31, May.
    2. Jie Tian & Jun Tong & Shi Luo, 2018. "Differential Steering Control of Four-Wheel Independent-Drive Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-18, October.
    3. Sara Abdallaoui & El-Hassane Aglzim & Ahmed Chaibet & Ali Kribèche, 2022. "Thorough Review Analysis of Safe Control of Autonomous Vehicles: Path Planning and Navigation Techniques," Energies, MDPI, vol. 15(4), pages 1-19, February.
    4. Jie Tian & Jie Ding & Yongpeng Tai & Ning Chen, 2018. "Hierarchical Control of Nonlinear Active Four-Wheel-Steering Vehicles," Energies, MDPI, vol. 11(11), pages 1-14, October.
    5. Hazel Si Min Lim & Araz Taeihagh, 2019. "Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities," Sustainability, MDPI, vol. 11(20), pages 1-28, October.
    6. Francesco Calise & Mário Costa & Qiuwang Wang & Xiliang Zhang & Neven Duić, 2018. "Recent Advances in the Analysis of Sustainable Energy Systems," Energies, MDPI, vol. 11(10), pages 1-30, September.

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