Joint human-automation decision making in road traffic management

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

Authors

Abstract

In this paper we explore automation bias in terms of joint decision making between humans and automation. In an experiment, participants made decisions, and indicated the reason for this decision, in a road traffic monitoring task with the aid of automation of varying reliability (i.e., 25% or 81%). Reliability level had a clear impact on the user's behavior: at low reliability, participants ignored automation suggestion and rely on their own decision making, whereas in the high reliability condition, participants tended to accept the automation suggestion (even if this was incorrect). Overall, performance is higher as a result of the human intervention that would be expected from automation alone, i.e., accuracy is in the region of 87-96% on all conditions. Performance is affected by the order in which the human and automation give their answers and how much detail they are required to provide. We consider these results in terms of a theory of joint decision making.

Details

Original languageEnglish
Title of host publicationProceedings of the Human Factors and Ergonomics Society 2017 Annual Meeting
Publication statusPublished - 1 Sep 2017
EventHuman Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017 - Austin, United States
Duration: 9 Oct 201713 Oct 2017

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Number1
Volume61
ISSN (Print)1071-1813

Conference

ConferenceHuman Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017
CountryUnited States
CityAustin
Period9/10/1713/10/17

ASJC Scopus subject areas