@inproceedings{49fc5539a50e4445877a747e25d72e69,
title = "Design Techniques for Exploring Inclusive Automotive Interaction Design in the Age of Vehicular Automation",
abstract = "With the emergence of self-driving vehicles, automotive interaction design is undergoing a seismic shift. Previously, vehicle interactions have been designed around the needs of the driver, who has been assumed to be sighted, while with the rise of automation, emerging automotive technologies will need to be designed around the future operator, who may be visually impaired or have other disabilities. This changing paradigm demands new thinking around the design of automotive user experiences. Within this paper, we survey automotive interaction design techniques by exploring our research. We describe how user enactments, focus groups, participatory design, and quasi-naturalistic studies are promising approaches in the development of emerging self-driving vehicles designed with the new, potentially disabled operator in mind. We then describe 12 best practices for their use. We believe a discussion of our experiences may benefit designers interested in more inclusive automotive interaction design.",
keywords = "Autonomous vehicles, blind, design methods, self-driving vehicles, vehicle interaction",
author = "Julian Brinkley and Huff, \{Earl W.\} and Aaron Gluck",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022 ; Conference date: 17-11-2022 Through 19-11-2022",
year = "2022",
doi = "10.1109/ICHMS56717.2022.9980641",
language = "English",
series = "Proceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "David Kaber and Antonio Guerrieri and Giancarlo Fortino and Andreas Nurnberger",
booktitle = "Proceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022",
address = "United States",
}