Trust Estimation for Autonomous Vehicles by Measuring Pedestrian Behavior in VR

被引：1

作者：

Masuda, Ryota ^{[1
]}

Hiraoka, Toshihiro ^{[1
]}

Ono, Shintaro ^{[2
]}

Suda, Yoshihiro ^{[1
]}

机构：

[1] Univ Tokyo, 4-6-1 Komaba,Meguro Ku, Tokyo, Japan

[2] Fukuoka Univ, 8-19-1 Nanakuma,Jonan Ku, Fukuoka, Japan

来源：

COMPANION OF THE ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, HRI 2023 | 2023年

关键词：

Automated Vehicles; Human-Automation Interaction; Trust In Automation; Deep Learning;

D O I：

10.1145/3568294.3580072

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This study proposes a method to estimate pedestrian trust in an automated vehicle (AV) based on pedestrian behavior. It conducted experiments in a VR environment where an AV approached a crosswalk. Participants rated their trust in the AV at three levels before/while they crossed the road. The level can be estimated by deep learning using their skeletal coordinates, position, vehicle position, and speed during the past four seconds. The estimation accuracy was 61%.

引用

页码：203 / 207

页数：5

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