A Scaling Method for Real-Time Monitoring of Mechanical Arm Admittance

被引：1

作者：

Antonin, Joly ^{[1
]}

Zheng Rencheng ^{[1
]}

Kimihiko, Nakano ^{[2
]}

机构：

[1] Univ Tokyo, Inst Ind Sci, Tokyo, Japan

[2] Univ Tokyo, Interfac Initiat Informat Studies, Tokyo, Japan

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS | 2015年

关键词：

Human factor; Driving behaviour; Mechanical arm admittance;

D O I：

10.1109/SMC.2015.274

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Dynamic of driver arm plays an important role in the understanding of driver intentions. Combined with mechanical driving variables and human-related parameters, it allows building a road safety system based on driving intensions and could possibly provide corrections to driving mistakes. Mechanical arm admittance is a driving related parameter which represents the reaction of driver facing a steering perturbation. It is used to state driver condition. If comparison of two mechanical arm admittance amplitudes permits knowing the difference of driver condition on the two trials, monitoring a driver in real-time provides only one mechanical arm admittance data. Then a calibration is needed to know the condition of the driver. In this study, a method for scaling mechanical arm admittance is proposed. Moreover, results indicate that this calibration has to be done individually.

引用

页码：1551 / 1556

页数：6

共 9 条

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