Design Techniques for Exploring Inclusive Automotive Interaction Design in the Age of Vehicular Automation

Julian Brinkley, Earl W. Huff, Aaron Gluck

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022
EditorsDavid Kaber, Antonio Guerrieri, Giancarlo Fortino, Andreas Nurnberger
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665452380
DOIs
StatePublished - 2022
Event3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022 - Orlando, United States
Duration: 17 Nov 202219 Nov 2022

Publication series

NameProceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022

Conference

Conference3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022
Country/TerritoryUnited States
CityOrlando
Period17/11/2219/11/22

Keywords

  • Autonomous vehicles
  • blind
  • design methods
  • self-driving vehicles
  • vehicle interaction

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