PhD Thesis: Attention management to improve fallback-readiness in conditional automated vehicles
This work explores the management of driver attention in Conditional Automated Driving (CAD) to improve situation awareness for safer control transitions. The research develops an attention management system that facilitates interleaved transitions between non-driving-related activities and vehicle supervision. The system is based on the encoded information of automation reliability to indicate the likelihood of an upcoming transition. The research addresses three research questions and presents a tool to prototype and evaluate the impacts of interfaces. The findings suggest that managed interruptions initiate a phase of interleaved attention, hinting towards improved situation awareness, and may benefit safety without negatively impacting usability.
Gerber, M. A. (2023). Attention management to improve fallback-readiness in conditional automated vehicles [Phd, Queensland University of Technology]. https://eprints.qut.edu.au/239712/
Supervised by Prof. Ronald Schroeter, Prof. Daniel Johnson & Prof. Andry Rakotonirainy