Subjective and objective descriptions of driving scenes in support of driver-automation interactions

Christopher Cabrall, Riender Happee, Joost de Winter

Research output: Contribution to conferencePosterScientific

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Abstract

Background: Recent advances in the growing domain of automated driving suggest the need for thoughtful design of human-computer interaction strategies. For example, human drivers can process scene variability on implicit levels, but automated systems require explicit rule-based judgments of similarity and difference. What level of abstraction an automation uses in its visual perception may mean the difference between effective human-automation communication, or “uncanny valley”-like conflicts leading to problems of automation disuse, misuse, or abuse. Purpose of study: In the present research, different quantifications (semantic coding vs. computer vision features) of driving scene-to-scene similarity and difference were compared against intuitive human judgments as a reference point for future human-automation interactions.
Original languageEnglish
Number of pages1
Publication statusPublished - 2016
EventHFES 2016: Annual Meeting Human Factors and Ergonomics Society : Human Factors and User Needs in Transport, Control, and the Workplace - Prague, Czech Republic
Duration: 26 Oct 201628 Oct 2016

Conference

ConferenceHFES 2016: Annual Meeting Human Factors and Ergonomics Society
Country/TerritoryCzech Republic
CityPrague
Period26/10/1628/10/16

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