Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (12): 3729-3739.doi: 10.13229/j.cnki.jdxbgxb.20230175

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Dynamic control for trajectory tracking of variable speed lane change in autonomous vehicles

Gang LIU1(),Qun FAN1,Xu YANG2,Hong-bin REN3   

  1. 1.School of Mechatronics Engineering,Shenyang Aerospace University,Shenyang 110136,China
    2.Liaoning Luping Machinery Co. ,Ltd. ,Tieling 112001,China
    3.School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China
  • Received:2023-02-27 Online:2024-12-01 Published:2025-01-24

Abstract:

A dynamic control strategy for variable speed lane change trajectory tracking was proposed. It includes a double PID longitudinal speed controller and a lateral model predictive controller using comprehensive evaluation indexes: lateral error, yaw rate, and side-slip angle. coefficients of each evaluation index based on the estimated tire-road friction coefficient and predicted vehicle status information. This allows achieving dynamic control between tracking accuracy and lateral stability. To verify the effectiveness of the algorithm, variable speed lane changing scenarios with high and low tire-road friction coefficients were designed, and CarSim and Simulink simulations were conducted. The simulation results demonstrate that the proposed dynamic control strategy realizes the dynamic adjustment of weight factors under different tire-road friction coefficients. It ensures smooth control output during lane changes, improves trajectory tracking control accuracy and lateral stability of unmanned vehicles simultaneously, and exhibits good coordination control effect.

Key words: vehicle engineering, dynamic control, variable speed lane change, model predictive control, adaptive working condition, longitudinal control

CLC Number: 

  • U463.6

Fig.1

Vehicle dynamics model"

Fig.2

Vehicle model in Frenet coordinate system"

Fig.3

Schematic diagram of speed change and lane change"

Fig.4

Flow chart of vertical controller"

Fig.5

Architecture diagram of controller co-simulation"

Table 1

Vehicle dynamics model parameters"

参数数值
整车质量m/kg1 413
质心与前轴间距lf/m1.015
质心与后轴间距lr/m1.895
车身绕Z轴的转动惯量Iz/(kg?m-2)1 536.7
前轮的侧偏刚度Cf/(N·rad-1)-148 970
后轮的侧偏刚度Cr/(N·rad-1)-82 204
车轮有效滚动半径r/m0.347

Fig.6

Estimation of road adhesion coefficient"

Fig.7

Horizontal position comparison"

Fig.8

Control performance analysis"

Table 2

Comparison of tracking accuracy indexes"

项目横向位移误差峰值/m横向误差RMS/m
可拓MPC0.280.08
动态控制0.090.04
优化效果/%67.950.0

Table 3

Comparison of lateral stability indexes"

指标

可拓

MPC

动态

控制

优化效果/%
横摆角速度误差峰值/[(°)·s-15.201.0480.0
横摆角速度误差RMS/[(°)·s-10.840.3064.3
质心侧偏角峰值/[(°)·s-10.012 60.003 473.0

Table 4

Comparison of front wheel angle"

前轮转角可拓MPC动态控制优化效果/%
峰值/(°)2.310.4580.5
RMS/(°)0.430.1858.1

Fig.9

Throttle-brake pressure output diagram"

Fig.10

Effect diagram of vehicle speed control"

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