Lateral tracking control mode switching strategy and evaluation method for intelligent vehicle
LIANG Jun1， LI Zheyu1， ZHANG Xing1， HUA Guodong2
1. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu 212013， China; 2. Jiangsu Smart Travel Future Automobile Research Institute Co., Ltd., Nanjing, Jiangsu 211111, China
Abstract：To solve the problem that in traditional switching strategies for lateral tracking control algorithms in intelligent vehicles, the model matching strategy was always in active state with consuming computational resources and reducing motion smoothness, a control mode switching strategy based on least squares support vector machine (LSSVM) was designed. By the strategy, the control modes were dynamically switched based on error assessment under varying operational conditions. The control effectiveness was evaluated from three aspects of safety, comfort and tracking accuracy. The optimal control amount was executed in real time based on a multi-objective optimization mathematical model. The simulation results show that by the switching strategy, the superior lateral tracking performance in intelligent vehicles can be achieved under varying conditions with path tracking deviation range of ±0.1 m, yaw rate fluctuation range of ±2 （°）/s and jerk value range of ±10 m/s3. Compared to traditional single control algorithms, the proposed strategy exhibits improved tracking accuracy, stability and comfort.
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2024, Vol. 45 
