Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (11): 3593-3603.doi: 10.13229/j.cnki.jdxbgxb.20240109

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Driver-automation cooperation oriented lane-keeping control employing model predictive control approach

Jun-hui ZHANG1,2,3,4(),Yu-xi LIU2,4,Xiao-man GUO2,4,Jun-ze LIU2,4,Yu-xuan DING2,4   

  1. 1.School of Electrical Engineering and Automation，Suzhou University of Technology，Suzhou 215500，China
    2.Wuxi Internet of Things Innovation Center Co. ，Ltd. ，Wuxi 214029，China
    3.Jiangsu Engineering Research Center of Industrial Robot Complex Process Intelligent Control，Suzhou 215500，China
    4.Kunshan Department，Jiangsu Internet of Things Innovation Center，Suzhou 215347，China
  • Received:2024-01-29 Online:2025-11-01 Published:2026-02-03

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Abstract:

In order to better describe the structure and behavior of the shared lane keeping assist system （LKAS）， and hence to enable the intelligent system to predict the driver's steering intention during the co-driving， a novel shared steering control algorithm based on situation prediction factor is thus proposed. Firstly， a driver steering model based on visual preview characteristics and neuromuscular dynamics is introduced. The parameters of such model are identified by particle swarm optimization （PSO） algorithm. By the integration of driver steering model and vehicle-road model， the closed-loop driver-vehicle-road model is established. Secondly， by employing model predictive control （MPC） framework， the decision-making of desired steering torque for shared LKAS is transformed into an online quadratic programming （QP） problem formulated as a quadratic objective function with multiple linear inequality constraints. Then， in order to achieve smooth transition of driving control authority， a driver-automation control authority model is designed using comprehensive preview error approach. Finally， the comparative experimental results demonstrate that by introducing the driver steering model， the intervention from intelligent system， negative intervention especially， can be effectively reduced to a certain extent， but the improved driver-automation friendliness is at the cost of sacrificing the accuracy of lateral motion control.

Key words: intelligent vehicle, shared autonomy, MPC, control authority decision, driver steering model

CLC Number: 

  • U461

Fig.1

Shared LKAS system design"

Fig.2

Road-vehicle model based on single-point preview"

Fig.3

Two-point preview model"

Fig.4

Driver steering model"

Table 1

Parameters of driver steering model"

参数KPKCτleadτlagτpKRKTτN
数值2.128.02.61.00.040.2720.50.1

Fig.5

Comparison of steering torques of the driver and driver steering model"

Fig.6

Lane departure reference model"

Fig.7

Driver-automation control authority decision model， where α=0.27,λ1=0.8,λ2=0.2"

Fig.8

Driver-in-the-loop platform and curved road"

Table 2

Parameters of vehicle dynamics"

参 数数值
整车质量m/kg1 650
质心绕z轴的转动惯量Iz /（kg?m2）3 234
车身宽度/m1.88
前轴与车辆质心之间的距离a/m1.4
后轴与车辆质心之间的距离b/m1.65
前轮的侧偏刚度Cf /（kN?rad-1）92
后轮的侧偏刚度Cr /（kN?rad-1）92
轮胎接触地面宽度ηt /m0.13
转向系等效阻尼系数Bs /（N?m?s?rad-1）0.57
转向系等效转动惯量Js /（kg?m2）0.05
转向传动比is16
道路宽度/m3.75
近视点预瞄距离/m5
远视点预瞄距离/m15
纵向速度vx /（km?h-1）30
采样周期/ms100

Fig.9

Comparison of lateral deviations"

Fig.10

Driver control authority"

Fig.11

Comparison of steering wheel angles"

Fig.12

Comparison of steering torques"

Fig.13

Comparison of co-driving effect of different models"

Fig.14

Comparison of co-driving effect of different strategies"

Table 3

Comparison of comprehensive performances"

指标项目JTJD,?phyJD,?psyJA
G策略DVR模型1.04119.58180.27108.11
G策略VR模型0.35125.37235.12180.61

Fig.15

Comparison of co-driving effect of different drivers"

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