Quantifying attentional demand of a lane-keeping task as the minimum required information in predictive processing
Kujala, T. (2021). Quantifying attentional demand of a lane-keeping task as the minimum required information in predictive processing. In DDI 2021 : 7th International Conference on Driver Distraction and Inattention : Book of Abstracts (pp. 54-57). Université Gustave Eiffel; SAFER Vehicle and Traffic Safety Centre at Chalmers; UNSW Sydney. https://ddi2020.sciencesconf.org/data/pages/Proceedings_DDI_211021.pdf
Date
2021Discipline
Koulutusteknologia ja kognitiotiedeKognitiotiedeLearning and Cognitive SciencesCognitive ScienceCopyright
© 2021 Université Gustave Eiffel; SAFER; UNSW Sydney
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Université Gustave Eiffel; SAFER Vehicle and Traffic Safety Centre at Chalmers; UNSW SydneyConference
International conference on driver distraction and inattentionIs part of publication
DDI 2021 : 7th International Conference on Driver Distraction and Inattention : Book of AbstractsKeywords
Original source
https://ddi2020.sciencesconf.org/data/pages/Proceedings_DDI_211021.pdfPublication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/103626752
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Related funder(s)
Research Council of FinlandFunding program(s)
Academy Project, AoFAdditional information about funding
The research was partly funded by Academy of Finland (Appropriate Uncertainty in Manual and Automated Driving/343259).License
Except where otherwise noted, this item's license is described as In Copyright