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.
|Title of host publication||Contemporary Ergonomics & Human Factors 2017|
|Editors||Rebecca Charles, John Wilkinson|
|Publisher||Chartered Institute of Ergonomics & Human Factors|
|Publication status||Published - 18 Dec 2018|
|Event||Ergonomics & Human Factors 2017 - Daventry, United Kingdom|
Duration: 25 Apr 2017 → 27 Apr 2017
|Conference||Ergonomics & Human Factors 2017|
|Period||25/04/17 → 27/04/17|
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.