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Acta Armamentarii ›› 2020, Vol. 41 ›› Issue (3): 585-594.doi: 10.3969/j.issn.1000-1093.2020.03.020

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Path Planning and Tracking Control of Autonomous Vehicle for Obstacle Avoidance

DENG Haipeng1, MA Bin1, ZHAO Haiguang2, L Liang1, LIU Yu1   

  1. (1.State Key Laboratory of Automobile Simulation and Control, Jilin University, Changchun 130025, Jilin, China;2.Chinese Research Academy of Environmental Science, Beijing 100012, China)
  • Received:2019-05-13 Revised:2019-05-13 Online:2020-05-11

Abstract: Emergency obstacle avoidance is one of the key points for autonomous driving system. A path planning controller based on non-linear model predictive control and a path tracking controller based on linear time-varying model predictive control are designed.In path planning controller,an obstacle-avoiding function is used to adjust the distance between the intelligent vehicle and obstacles by calculating the value of obstacle-avoiding function.A new route is supposed to be planned,which can not only keep away from obstacles but also decrease the deviations from the global course,by considering the different weights of obstacle-avoiding function and the planning error. In path tracking controller,the solution of linear time-varying model predictive control is converted into a positive-definite quadratic program.And then the desired steering angles of front wheel are calculated by using the reference trajectory and orientation angle of vehicle center. The results show that the obstacle-avoiding controller has strong robustness and the path tracking controller has better performance in controlling accuracy and vehicle dynamics stability when a vehicle travels at 60 km/h,80 km/h,or 100 km/h. The maximal side-slip angle is no more than 1°,and the maximal deviation of yaw angle is less than 2.5°.Obstacle avoiding action occurs in advance with the increase in velocity of autonomous vehicle. In addition,the dual-MPC controller is adaptive to the circumstance of multi-obstacles avoidance as well,which can be easily demonstrated by the small deviation of yaw angles and small side-slip angles.Key

Key words: autonomousvehicle, obstacleavoidance, pointmassmodelofvehicle, modelpredictivecontrol, pathplanningandtracking

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