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Out of Sight, Out of Mind? Investigating People's Assumptions About Object Permanence in Self-Driving Cars
Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. (Cognition & Interaction Lab)ORCID iD: 0000-0003-0098-5391
Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Arts and Sciences.
Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. (Cognition & Interaction Lab)ORCID iD: 0000-0001-6883-2450
2023 (English)In: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, New York, NY, USA: ACM Digital Library, 2023, p. 602-606Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Safe and efficient interaction with autonomous road vehicles requires that human road users, including drivers, cyclists, and pedestrians, understand differences between the capabilities and limitations of self-driving vehicles and those of human drivers. In this study, we explore how people judge the ability of self-driving cars versus human drivers to keep track of out-of-sight objects by engaging online study participants in cognitive perspective taking toward a car in an animated traffic scene. The results indicate that people may expect self-driving cars to have similar object permanence capability as human drivers. This finding is important because unmet expectations on autonomous road vehicles can result in undesirable interaction outcomes, such as traffic accidents.

Place, publisher, year, edition, pages
New York, NY, USA: ACM Digital Library, 2023. p. 602-606
Keywords [en]
human-vehicle interaction, perceptual belief, mental state attribution, perspective taking
National Category
Human Computer Interaction Robotics
Identifiers
URN: urn:nbn:se:liu:diva-197635DOI: 10.1145/3568294.3580156ISI: 001054975700119Scopus ID: 2-s2.0-85150444646ISBN: 9781450399708 (print)OAI: oai:DiVA.org:liu-197635DiVA, id: diva2:1794308
Conference
2023 ACM/IEEE International Conference on Human-Robot Interaction, Stockholm, Sweden, March 13 - 16, 2023
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Research Council, 2022-04602
Note

Funding: ELLIIT, the Excellence Center at Linkoping-Lund in Information Technology; Swedish Research Council (VR) grant [2022-04602]

Available from: 2023-09-05 Created: 2023-09-05 Last updated: 2023-10-11Bibliographically approved

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Thellman, SamPettersson, MaxZiemke, Tom

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Thellman, SamHolmgren, AkselPettersson, MaxZiemke, Tom
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Citation style
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