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Research on Hybrid Control Strategy for Path Tracking of Autonomous Vehicles
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Zhaokai Li, Xinning Liu, Guoxuan Peng, Xue Sun, Tao Chen
Automobile Technology | 2024, (3) : 37 - 46
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Automobile Technology | 2024, (3): 37-46
Research on Hybrid Control Strategy for Path Tracking of Autonomous Vehicles
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Zhaokai Li, Xinning Liu, Guoxuan Peng, Xue Sun, Tao Chen
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  • Chang’an University, Xi’an 710018
Published: 2024-03-24 doi: 10.19620/j.cnki.1000-3703.20230737
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For the fact that single control algorithm cannot simultaneously meet the requirements of autonomous vehicles for path tracking accuracy and controller solving speed, this paper proposed a hybrid control strategy based on Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC). The strategy used an LQR in the low-speed condition and an MPC algorithm in the high-speed condition, on the basis of which a switching mechanism of the control algorithm based on a Finite State Machine (FSM) was designed and the control parameters were optimized by Genetic Algorithm (GA). The hybrid control strategy was simulated and verified based on CarSim and MATLAB/Simulink simulation platforms, and the real vehicle test was further completed. The experimental results show that the designed hybrid control strategy can reduce the computation time on the basis of improving the tracking accuracy, and the average lateral error and average heading error are reduced by 26.3% and 39.6%, respectively, and the average computation time is reduced by 10.9% compared with the single control algorithm.

Path tracking  /  Linear Quadratic Regulator (LQR)  /  Model Predictive Control (MPC)  /  Finite State Machine (FSM)  /  Genetic Algorithm (GA)
Zhaokai Li, Xinning Liu, Guoxuan Peng, Xue Sun, Tao Chen. Research on Hybrid Control Strategy for Path Tracking of Autonomous Vehicles[J]. Automobile Technology, 2024 , (3) : 37 -46 . DOI: 10.19620/j.cnki.1000-3703.20230737
Year 2024 volume Issue 3
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doi: 10.19620/j.cnki.1000-3703.20230737
  • Online Date:2025-12-23
  • Published:2024-03-24
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    Chang’an University, Xi’an 710018
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表12种不同金属材料的力学参数

Family
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Number of
genus
种数
Number of
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占总种数比例
Percentage of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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