Automobile Active Obstacle Avoidance System Based on Model Predictive Control
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    Abstract:

    In order to ensure the safety of vehicle driving,an active obstacle avoidance system for intelligent ve- hicles was built in this study,which included four parts:environmental perception,dangerous situation assess- ment,path decision-making and control execution. Based on the improved artificial potential field model,a path planning module was constructed which consisted of the road boundary repulsion potential field,dynamic obsta- cle repulsion potential field and gravitational potential field. At the same time,the front wheel declination was used as the control variable to establish the vehicle dynamics model,and the model prediction algorithm was used to track the planning path. The results of the joint simulation of CarSim/Simulink show that the established model predictive control is better than the driver's preview control,which has better tracking effect on the path and improves the tracking accuracy,and finally realizes the active obstacle avoidance of the automobile.

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杨丰萍,谢梦莎,彭理群,郑文奇,刘锋.基于模型预测控制的汽车主动避障系统[J].华东交通大学学报英文版,2020,37(1):70-76.
Yang Fengping, Xie Mengsha, Peng Liqun, Zheng Wenqi, Liu Feng. Automobile Active Obstacle Avoidance System Based on Model Predictive Control[J]. JOURNAL OF EAST CHINA JIAOTONG UNIVERSTTY,2020,37(1):70-76

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  • Online: May 11,2021
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