Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (8): 2404-2409.doi: 10.13229/j.cnki.jdxbgxb.20220377

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Active collision avoidance method of driverless vehicle based on partheno genetic algorithm

Guo-hong TIAN(),Peng-jie DAI   

  1. School of Automobile and Traffic Engineering,Liaoning University of Technology,Jinzhou 121001,China
  • Received:2022-04-07 Online:2023-08-01 Published:2023-08-21

Abstract:

To effectively improve the active safety of autonomous vehicles, a single parent genetic algorithm based active collision avoidance method for autonomous vehicles is proposed. Construct a dynamic model for autonomous vehicles using normalized azimuth evaluation functions. Based on the predicted behavior trajectory, pre braking is taken in advance, and a single point gene replication strategy is introduced to implement genetic operations with the goal of minimizing the path from the initial point to the endpoint, in order to obtain the optimal solution for autonomous vehicle active collision avoidance. The simulation results show that this method can plan a reliable turning collision avoidance path under emergency conditions, with stable vehicle state parameters, small path deviation, and strong robustness to different vehicle speeds and turning paths.

Key words: partheno genetic algorithm, driverless car, active collision avoidance, dynamic model, behavior tracking, moment constraint

CLC Number: 

  • U461.2

Table 1

Dynamics parameters of driverless vehicle"

动力学参数数值
整车质量/kg1824
转动惯量/(kg·m24219
质心至前轴间距/m1.295
质心至后轴间距/m1.689
质心高度/m0.55
车身宽度/m1.623

Fig.1

Comparison of simulation results of three methods of straight collision avoidance"

Fig.2

Comparison of simulation results of yaw rate and centroid sideslip angle using three methods"

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