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Integrated Path Tracking Control of Steering and Differential Braking Based on Tire Force Distribution

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  • Control Theory and Applications
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Abstract

The integrated path tracking control of steering and differential braking can significantly improve the tracking performance of autonomous vehicles in collision avoidance in the limit conditions. However, the distribution of steering and braking control rights has not received sufficient attention in the existing control method. The distribution strategy is relatively simple and lacks theoretical support. Therefore, aiming at the problem of the distribution of steering and braking control rights in the integrated path tracking control, a tire force distribution rule is proposed in this study, and a path tracking control method based on holistic model predictive control (MPC) is designed. To describe the coupling and strong nonlinearity of tire dynamics, a UniTire tire model with combined slip conditions is established in the controller model. Furthermore, the nonlinear controller model is linearized by Taylor expansion and a linear time-varying MPC controller is designed to improve the real-time performance of the system. Finally, the effectiveness of the proposed method is verified via the co-simulation tests of CarSim and Simulink. The simulation tests at the different speeds and road friction coefficients demonstrate the superiority of the proposed method in path tracking performance, lateral stability, and traffic efficiency.

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Funding

The work is supported by the National Key Research and Development Program of China (Nos. 2018YFE0192900 and 2019YFC0605300), the Fundamental Research Funds for the Central Universities (FRF-IC-20-02), and Guangdong Basic and Applied Basic Research Foundation (No.2019A1515111015).

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, University of Science and Technology Beijing, 100083, Beijing, China

    Guodong Wang, Li Liu, Yu Meng, Qing Gu & Guoxing Bai

  2. Shunde Graduate School of University of Science and Technology Beijing, Foshan, Guandong, 528300, China

    Qing Gu

Authors
  1. Guodong Wang
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  2. Li Liu
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  3. Yu Meng
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  4. Qing Gu
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  5. Guoxing Bai
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Corresponding author

Correspondence to Yu Meng.

Additional information

Guodong Wang received his M.S. degree in automotive engineering from Changchun University of Technology, Jilin Province, China. He is currently pursuing a Ph.D. degree in mechanical engineering at University of Science and Technology Beijing, Beijing, China. His research interests include autonomous driving technology and model predictive control.

Li Liu received his Ph.D. degree in mechanical engineering from the University of Science and Technology Beijing, Beijing, China, in 2012, where he is currently a Professor with the School of Mechanical Engineering. His research interests include the control of driverless vehicles and intelligent transportation.

Yu Meng received his M.S. and Ph.D. degrees in computer science and technology from Jilin University, Changchun, China, in 2007. He is currently an Associate Professor with the School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China. His research interests include computer vision and intelligent vehicle.

Qing Gu received her Ph.D. degree in intelligent traffic engineering from Beijing Jiaotong University, Beijing, China, in 2014. She is currently an Assistant Professor with the School of Mechanical Engineering, University of Science and Technology Beijing, Beijing. Her research interests include systems modeling, control, and optimization with application in intelligent transportation systems.

Guoxing Bai is currently a postdoctoral fellow at the School of Mechanical Engineering, University of Science and Technology Beijing. In 2014, he received a bachelor’s degree in vehicle engineering from Northeastern University, Shenyang, China. In 2020, he received a Ph.D. degree in Mechanical Engineering from University of Science and Technology Beijing, Beijing, China. He is mainly engaged in the research of vehicle unmanned driving. His specific research interests include path tracking control, obstacle avoidance control, automatic parking control, etc.

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Wang, G., Liu, L., Meng, Y. et al. Integrated Path Tracking Control of Steering and Differential Braking Based on Tire Force Distribution. Int. J. Control Autom. Syst. 20, 536–550 (2022). https://doi.org/10.1007/s12555-021-0117-x

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  • DOI: https://doi.org/10.1007/s12555-021-0117-x

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