Identification Method for Occupant Personalized Ride Comfort of Autonomous Vehicles

被引：0
|
作者：
Lan F. [1 ]
Li S. [1 ]
Chen J. [1 ]
Shen Z. [2 ]
机构：
[1] School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou
[2] Guangzhou Xiaopeng Motors Technology Co., Ltd., Guangzhou
来源：
Qiche Gongcheng/Automotive Engineering | 2021年 / 43卷 / 08期
关键词：
Autonomous driving; Evaluation; Identification; Occupant comfort; Personalization;
D O I：
10.19562/j.chinasae.qcgc.2021.08.007
中图分类号：
学科分类号：
摘要：
For the problem that autonomous vehicle trajectory planning control algorithm cannot meet the personalized comfort of occupants, combining natural driving data and occupant comfort requirements, a method for identifying occupants' personalized comfort is established. Firstly, the subjective comfort evaluation method is determined. Based on the standard ISO2631, frequency domain and time domain weighted filter functions are built. Subjective and objective characteristic parameters of occupant comfort of autonomous vehicles are extracted and the relationship between occupant's personalized comfort and autonomous vehicle driving planning parameters is identified. Then, a natural driving data acquisition platform is established to collect the driving parameters and subjective and objective parameters that affect comfort. Factor analysis is used to reduce the dimensions of driving parameters to obtain three-way motion (lateral impact, longitudinal acceleration, and vertical vibration), driving risk and efficiency influencing factors. Finally, the weighted analysis method is used to identify the model, and the Kalman filter algorithm is applied to quickly and accurately identify the individual needs of the occupant, and the weighted root-mean-square threshold of comfort is obtained. The identification results show that the correlation between the subjective and objective comfort of the occupant reaches 85.81%; the three-way motion factor has a greater impact on the occupant comfort than the driving risk and efficiency factors; the identification rate of occupant personalized comfort is as high as 93%. The study can provide theoretical support for constructing personalized trajectory planning control algorithm considering occupant comfort. © 2021, Society of Automotive Engineers of China. All right reserved.
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页码：1168 / 1176and1215
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