Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (9): 2847-2857.doi: 10.13229/j.cnki.jdxbgxb.20250242

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Humanized stop⁃and⁃go control strategy for adaptive cruise system of pure electric vehicle

Tian-jun SUN1,2,3(),Hui-zhe YANG2,Rong-gui CAI2,Jia-yi FENG3(),Rui RAN2,Bin LIU4   

  1. 1.National Key Laboratory of Automotive Chassis Integration and Bionics，Jilin University，Changchun 130022，China
    2.College of Automotive Engineering，Jilin University，Changchun 130022，China
    3.Ministry of Industry and Information Technology Equipment Industry Development Center，Beijing 100846，China
    4.FAW General R&D Institute，Changchun 130013，China
  • Received:2025-03-24 Online:2025-09-01 Published:2025-11-14
  • Contact: Jia-yi FENG E-mail:sun_tj@jlu.edu.cn;fengjiayi@eidc.org.cn

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Abstract:

Addressing the issue of insufficient adaptation to driving styles in the traditional adaptive cruise system of pure electric vehicles， a humanized stop-and-go control strategy based on driving behavior characteristics was proposed. Firstly， real driver stop-and-go data were analyzed and features extracted， and construction of a driving style classification model using principal component analysis and the K-Means++ algorithm. Secondly， a two-layer control architecture was designed to implement the human-like control logic for switching between driving and braking. Thirdly， a humanization factor was designed based on Bayesian linear regression and maximum entropy inverse optimization methods. Finally， the consistency between the proposed method and real drivers' control behaviors was validated through simulation tests aralysis.

Key words: automotive engineering, pure electric vehicles, adaptive cruise control, stop-and-go control, humanized decision-making control

CLC Number: 

  • U461.1

Fig.1

Driving behavior parameter distribution in lead vehicle absent start/stop scenarios"

Fig.2

Data collection for stop-and-go experiments based on driving simulator"

Table 1

Experimental acquisition parameters table"

类别参数名称符号单位
自车运动信息自车车速vhkm/h
自车纵向加速度ahm/s2
自车纵向加加速度jhm/s3
前车运动信息前车车速vfkm/h
前车纵向加速度afm/s2
相对运动信息与前车相对距离dm
与前车相对速度Δvkm/h
与前车相对加速度Δam/s2

Fig.3

Principal component variance contribution rate and cumulative variance contribution rate of characteristic parameters"

Fig.4

Three types of drivers feature parameter distribution histogram"

Fig.5

Workshop longitudinal following diagram"

Fig.6

Driver speed-following distance chart for different driving styles"

Table 2

Time headway bayesian linear regression fitting parameters for different driving style"

驾驶员类型车头时距拟合值车头时距拟合方差/10-5
第1类1.273 32.143 6
第2类0.943 62.251 2
第3类0.717 62.214 9

Table 3

Multi-objective weight parameter value table for three types of driving styles"

驾驶风格δΔδδΔvδahδa˙des
第1类4.156 77.123 919.826 430.204 4
第2类7.462 68.773 07.763 45.419 3
第3类7.513 714.828 20.528 90.732 9

Fig.7

Comparison chart between initialized ACC and type 1 driving style humanized ACC outputs"

Fig.8

Comparison chart between initialized ACC and type 2 driving style humanized ACC outputs"

Fig.9

Comparison chart between initialized ACC and type 3 driving style humanized ACC outputs"

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