Handling Trust Between Drivers and Automated Vehicles for Improved Collaboration

被引：1
|
作者：
Azevedo-Sa, Hebert [1 ]
Yang, X. Jessie [1 ]
Robert, Lionel P., Jr. [1 ]
Tilbury, Dawn M. [1 ]
机构：
[1] Univ Michigan, Ann Arbor, MI 48109 USA
来源：
HRI '21: COMPANION OF THE 2021 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION | 2021年
关键词：
Trust in Automation; Human-robot teaming; Driving simulation; INTEGRATIVE MODEL;
D O I：
10.1145/3434074.3446358
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Advances in perception and artificial intelligence technology are expected to lead to seamless interaction between humans and robots. Trust in robots has been evolving from the theory on trust in automation, with a fundamental difference: unlike traditional automation, robots could adjust their behaviors depending on how their human counterparts appear to be trusting them or how humans appear to be trustworthy. In this extended abstract I present my research on methods for processing trust in the particular context of interactions between a driver and an automated vehicle, which has the goal of achieving higher safety and performance standards for the team formed by those human and robotic agents.
引用
收藏
页码：589 / 591
页数：3
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