Parameter Setting and Driver Acceptability Evaluation of Steering Assistance System Using Impedance Control by Damping Ratio

被引:0
|
作者
Hayakawa, Soichiro [1 ]
Ikeura, Ryojun [1 ]
机构
[1] Mie Univ, Grad Sch Engn, 1577 Kuriyamachiya Cho, Tsu, Mie 5148507, Japan
关键词
impedance control; steering assistance sys-tem; driver acceptability; damping ratio; MANIPULATION;
D O I
10.20965/jrm.2023.p0694
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this paper, we introduce an adaptation to steering assistance systems for providing impedance control. We also suggest using the damping ratio as a design guideline for the parameters of the impedance control. In our research, experiments were conducted with experimental participants using a driving simulator implementing the suggested steering assistance system. As a result of both subjective and objective evaluations, it was found that the suggested steering assistance system is better accepted by drivers than the conventional system. Moreover, the use of the damping ratio as an evaluation index facilitates the design of the impedance parameters. These results indicate the effectiveness of our suggested system.
引用
收藏
页码:694 / 702
页数:9
相关论文
共 24 条
  • [21] A Review: Control Area Network (CAN) based Intelligent Vehicle System for Driver Assistance using Advanced RISC Machines (ARM)
    Jadhav, Ashutosh U.
    Wagdarikar, N. M.
    2015 INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING (ICPC), 2015,
  • [22] EVALUATION OF DAMPING RATIO OF OIL-FILM BEARING SYSTEM BY USING MODAL OPEN LOOP TRANSFER FUNCTION
    Fujiwara, Hiroyuki
    Matsushita, Osami
    Oyama, Hiroto
    8TH IFTOMM INTERNATIONAL CONFERENCE ON ROTOR DYNAMICS (IFTOMM ROTORDYNAMICS 2010), 2010, : 157 - 163
  • [23] How do we share the "control" when using the haptic shared control for an advanced driver-assistance system? -Direct HSC and Indirect HSC-
    Hiraoka, Toshihiro
    IFAC PAPERSONLINE, 2019, 52 (19): : 61 - 66
  • [24] Parameter identification and robust vibration control of a truck driver's seat system using multi-objective optimization and genetic algorithm
    Zhao, Yuli
    Alashmori, Mohammed
    Bi, Fengrong
    Wang, Xu
    APPLIED ACOUSTICS, 2021, 173