Analysing Driver (In)Attentiveness : Towards a Cognitive Complexity Model Combining Visuospatial and Interactional Parameters : 8th International Conference on Driver Distraction and Inattention (DDI 2022), Gothenburg, Sweden, October 19-20, 2022
(2022) International Conference on Driver Distraction and Inattention- Abstract
- We investigate the role of visuospatial environmental cues on driver (in)attention in everyday naturalistic driving situations. We develop a cognitive model of visuospatial complexity incorporating two critical aspects influencing visual (in)attention: (1) multimodal interaction mechanisms such as gesture, joint attention amongst roadside stakeholders (e.g. pedestrians, cyclists, drivers); and (2) visuospatial environmental features such as clutter, motion, environmental structure. Our research emphasises the manner in which a cognitive human-factors guided model to analyse attentiveness can be applied to systematically explore the effects of a combination of environmental and interactional characteristics on visual attention in... (More)
- We investigate the role of visuospatial environmental cues on driver (in)attention in everyday naturalistic driving situations. We develop a cognitive model of visuospatial complexity incorporating two critical aspects influencing visual (in)attention: (1) multimodal interaction mechanisms such as gesture, joint attention amongst roadside stakeholders (e.g. pedestrians, cyclists, drivers); and (2) visuospatial environmental features such as clutter, motion, environmental structure. Our research emphasises the manner in which a cognitive human-factors guided model to analyse attentiveness can be applied to systematically explore the effects of a combination of environmental and interactional characteristics on visual attention in naturalistic driving. We position the application of the developed cognitive model to serve a foundational purpose in the training and testing of novel driver assistance technologies, e.g., from the viewpoint of systematic compliance with human-centered design guidelines. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/aa1381f2-1da7-4c79-93dc-653aaa3fcac5
- author
- Kondyli, Vasiliki LU and Bhatt, Mehul
- publishing date
- 2022
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- visual attention, multimodality, naturalistic studies, embodied interactions, driving, cognitive technologies, Psychology, Psykologi, Computer and Information Sciences, Data- och informationsvetenskap
- conference name
- International Conference on Driver Distraction and Inattention
- conference location
- Gothenburg, Sweden
- conference dates
- 2022-10-19 - 2024-12-20
- language
- English
- LU publication?
- no
- id
- aa1381f2-1da7-4c79-93dc-653aaa3fcac5
- alternative location
- http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-100521
- http://oru.diva-portal.org/smash/get/diva2:1686343/FULLTEXT01.pdf
- date added to LUP
- 2024-12-18 15:15:05
- date last changed
- 2025-04-04 13:59:57
@misc{aa1381f2-1da7-4c79-93dc-653aaa3fcac5,
abstract = {{We investigate the role of visuospatial environmental cues on driver (in)attention in everyday naturalistic driving situations. We develop a cognitive model of visuospatial complexity incorporating two critical aspects influencing visual (in)attention: (1) multimodal interaction mechanisms such as gesture, joint attention amongst roadside stakeholders (e.g. pedestrians, cyclists, drivers); and (2) visuospatial environmental features such as clutter, motion, environmental structure. Our research emphasises the manner in which a cognitive human-factors guided model to analyse attentiveness can be applied to systematically explore the effects of a combination of environmental and interactional characteristics on visual attention in naturalistic driving. We position the application of the developed cognitive model to serve a foundational purpose in the training and testing of novel driver assistance technologies, e.g., from the viewpoint of systematic compliance with human-centered design guidelines.}},
author = {{Kondyli, Vasiliki and Bhatt, Mehul}},
keywords = {{visual attention; multimodality; naturalistic studies; embodied interactions; driving; cognitive technologies; Psychology; Psykologi; Computer and Information Sciences; Data- och informationsvetenskap}},
language = {{eng}},
title = {{Analysing Driver (In)Attentiveness : Towards a Cognitive Complexity Model Combining Visuospatial and Interactional Parameters : 8th International Conference on Driver Distraction and Inattention (DDI 2022), Gothenburg, Sweden, October 19-20, 2022}},
url = {{http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-100521}},
year = {{2022}},
}