A Human Factors Approach to Enhanced Machine Learning in Cars

Joseph Smyth, Stewart Birrell, Lech Birek, Kris Kobylinski, Alex Mouzakitis, P. Jennings

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

Using machine learning techniques, it is possible to learn and subsequently automate certain driver-focused features in consumer vehicles. A human factors approach is taken to review current machine learning systems. Subsequently, it is found that current methods used for machine learning involve long learning times and might not be sufficient to grasp a true understanding of interaction, routine and feature use - a new method is proposed. Issues surrounding trust and acceptance in automation are also explored and recommendations made.
Original languageEnglish
Title of host publication Contemporary Ergonomics & Human Factors 2017
EditorsRebecca Charles, John Wilkinson
PublisherChartered Institute of Ergonomics & Human Factors
ISBN (Electronic)978-1-5272-0762-2
Publication statusPublished - 18 Dec 2018
Externally publishedYes
EventErgonomics & Human Factors 2017 - Daventry, United Kingdom
Duration: 25 Apr 201727 Apr 2017

Conference

ConferenceErgonomics & Human Factors 2017
CountryUnited Kingdom
CityDaventry
Period25/04/1727/04/17

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  • Cite this

    Smyth, J., Birrell, S., Birek, L., Kobylinski, K., Mouzakitis, A., & Jennings, P. (2018). A Human Factors Approach to Enhanced Machine Learning in Cars. In R. Charles, & J. Wilkinson (Eds.), Contemporary Ergonomics & Human Factors 2017 Chartered Institute of Ergonomics & Human Factors.