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Bridging the gap between human visual anticipation and autonomous systems through the use of a vector addition model

Khoury, Jason and Blätter, Colin Bridging the gap between human visual anticipation and autonomous systems through the use of a vector addition model. (2020) In: 1st International Conference on Cognitive Aircraft Systems - ICCAS 2020, 18 March 2020 - 19 March 2020 (Toulouse, France). (Unpublished)

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Abstract

Visual anticipation is an essential cognitive function in that it is necessary for action and is considered a key feature of Endsley’s situational awareness model (1995, 2015). In recent decades, both research and industry have shown a growing interest in autonomous vehicles and, in this context, anticipation raises new questions. Indeed, human performances in automation situations decrease (e.g., complacency, degradation of skills and loss of situational awareness). Various causes are described by Victor et al. (2018), but an important one is the operators’ gap and misconceptions in their mental models of automated systems (Sarter & Woods, 1994). Surprised by automation; they do not know what behaviour the system will produce (Parasuraman et al., 2008), leading to inappropriate and therefore dangerous reactions. The objective is then to identify the mechanisms of visual anticipation to model how individuals anticipate events. Such modelling will facilitate the implementation of autonomous system anticipation algorithms that are more compatible with the mental model of users. The anticipation mechanism that has been firmly identified is called representational momentum (RM). Numerous studies have shown that the RM is sensitive to factors present in the context of driving a vehicle. And while some factors promote anticipation, others hinder it.

Item Type:Invited Conference
Audience (conference):International conference without published proceedings
Uncontrolled Keywords:
Institution:Other partners > École de l'air (FRANCE)
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Deposited On:09 May 2021 16:18

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