Biblio
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Utilizing ACT-R to investigate interactions between working memory and visuospatial attention while driving.
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2021. (POSTER PRESENTATION) Utilizing ACT-R to investigate interactions between working memory and visuospatial attention while driving at 2021 ICCM - International Conference on Cognitive Modeling, July 08, 2021
Investigating Effects of a n-back Task on Decision-Making using Eye-Tracking in a Driving Simulator.
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2021. ‘Investigating Effects of a n-back Task on Decision-Making using Eye-Tracking in a Driving Simulator’ at TeaP – Tagung Experimentell Arbeitender Psychologen, Mar 15, 2021
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2021.
I Spy with My Mental Eye – Analyzing Compensatory Scanning in Drivers with Homonymous Visual Field Loss. Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021).
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2021.
Utilizing ACT-R to investigate interactions between working memory and visuospatial attention while driving. Proceedings of the Annual Meeting of the Cognitive Science Society. 43(1)
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2021. In an effort towards predicting mental workload while driving, previous research found interactions between working memory load and visuospatial demands, which complicates the accurate prediction of momentary mental workload. To investigate this interaction, the cognitive concepts working memory load and visuospatial attention were integrated into a cognitive driving model using the cognitive architecture ACT-R. The model was developed to safely drive on a multi-lane highway with ongoing traffic while performing a secondary n-back task using speed signs. To manipulate visuospatial demands, the model must drive through a construction site with reduced lane-width in certain blocks of the experiment. Furthermore, it is able to handle complex driving situations such as overtaking traffic while adjusting the speed according to the n-back task. The behavioral results show a negative effect on driving performance with increasing task difficulty of the secondary task. Additionally, the model indicates an interaction at a common, task-unspecific level.
A Causal Model of Intersection-Related Collisions for Drivers With and Without Visual Field Loss. In Proceedings of the 2021, International Conference on Human-Computer Interaction.
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2021.
A causal model of intersection-related collisions for drivers with and without visual field loss. In Proceedings of the 23rd HCI International Conference (Ed.).
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2021.
I Spy with My Mental Eye: Analyzing Compensatory Scanning in Drivers with Homonymous Visual Field Loss. Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021). :552–559.
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2021. Drivers with visual field loss show a heterogeneous driving performance due to the varying ability to compensate for their perceptual deficits. This paper presents a theoretical investigation of the factors that determine the development of adaptive scanning strategies. The application of the Saliency-Effort-Expectancy-Value (SEEV) model to the use case of homonymous hemianopia in intersections indicates that a lack of guidance and a demand for increased gaze movements in the blind visual field aggravates scanning. The adaptation of the scanning behavior to these challenges consequently requires the presence of adequate mental models of the driving scene and of the individual visual abilities. These factors should be considered in the development of assistance systems and trainings for visually impaired drivers.