Small Talk, Big Impact? LLM-based Conversational Agents to Mitigate Passive Fatigue in Conditional Automated Driving
Cockram, Lewis, Yu, Yueteng, Pardo Gaytan, Jorge, Li, Xiaomeng, Rakotonirainy, Andry, Kuo, Jonny, Demmel, Sebastien, Lenné, Michael G., & Schroeter, Ronald (2026) Small Talk, Big Impact? LLM-based Conversational Agents to Mitigate Passive Fatigue in Conditional Automated Driving. In Oliver, Nuria, Shamma, David A., Candello, Heloisa, Cesar, Pablo, Lopes, Pedro, Bozzon, Alessandro, et al. (Eds.) CHI '26: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM), United States of America.
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Description
Passive fatigue during conditional automated driving can compromise driver readiness and safety. This paper presents findings from a test-track study with 40 participants in a real-world automated driving scenario. In this scenario, a Large Language Model (LLM) based conversational agent (CA) was designed to check in with drivers and re-engage them with their surroundings. Drawing on in-car video recordings, sleepiness ratings and interviews, we analysed how drivers interacted with the agent and how these interactions shaped alertness. Results show the CA is helpful for supporting vigilance during passive fatigue. Thematic analysis of acceptability further revealed three user preference profiles that implicate future intention to use CAs. Positioning empirically observed profiles within existing CA archetype frameworks highlights the need for adaptive design sensitive to diverse user groups. This work underscores the potential of CAs as proactive Human–Machine Interface (HMI) interventions, demonstrating how natural language can support context-aware interaction during automated driving.
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| ID Code: | 263229 | ||||||||||||
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| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||||||||||
| Series Name: | Conference on Human Factors in Computing Systems - Proceedings | ||||||||||||
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| Measurements or Duration: | 18 pages | ||||||||||||
| Event Title: | CHI Conference on Human Factors in Computing Systems 2026 | ||||||||||||
| Event Dates: | 2026-04-13 - 2026-04-17 | ||||||||||||
| Event Location: | Barcelona, Spain | ||||||||||||
| Keywords: | Human-Machine Interaction, Conversational AI, Automated Driving, Passive fatigue, Human-agent Collaboration, Attention management, Natural Language Interaction | ||||||||||||
| DOI: | 10.1145/3772318.3790972 | ||||||||||||
| ISBN: | 979-8-4007-2278-3 | ||||||||||||
| Pure ID: | 214999979 | ||||||||||||
| Divisions: | Current > Research Centres > Centre for Future Mobility/CARRSQ Current > QUT Faculties and Divisions > Faculty of Health Current > Schools > School of Psychology & Counselling |
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| Funding Information: | This research was undertaken under the QUT Industry Chair in Empathic Machines, in collaboration with and co-funded by industry partner Seeing Machines Ltd. Through participation in the National Industry PhD Program (NIPP), it has also been co-funded by the Department of Education. The Australian Research Council also provided financial support for this project through the Australian Research Council Industrial Transformation Training Centre for Automated Vehicles in Rural and Remote Regions (IC230100001). We thank the Queensland Department of Transport and Main Roads for providing access to the highly automated prototype vehicle Zoe2. We also thank the entire research team for their contributions, in particular the safety drivers who ensured operational safety throughout the study. We further acknowledge Sean Baek from the Faculty of Science for his support in software development, the research assistants who supported data collection, and the staff at the RACQ Mobility Centre for their support and understanding during the on-track data collection. | ||||||||||||
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| Copyright Owner: | 2026 Copyright held by the owner/author(s). | ||||||||||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||||||||||
| Deposited On: | 16 Feb 2026 16:23 | ||||||||||||
| Last Modified: | 09 Nov 2026 15:48 |
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