A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task

Jami Joonas Olavi Pekkanen, Otto Lappi, Paavo Rinkkala, Niko Samuel Tuhkanen, Roosa Frantsi, Kari Heikki Ilmari Summala

Research output: Contribution to journalArticleScientificpeer-review

Abstract

We present a computational model of intermittent visual sampling and locomotor control in a simple yet representative task of a car driver following another vehicle. The model has a number of features that take it beyond the current state of the art in modelling natural tasks, and driving in particular. First, unlike most control theoretical models in vision science and engineering—where control is directly based on observable (optical) variables—actions are based on a temporally enduring internal representation. Second, unlike the more sophisticated engineering driver models based on internal representations, our model explicitly aims to be psychologically plausible, in particular in modelling perceptual processes and their limitations. Third, unlike most psychological models, it is implemented as an actual simulation model capable of full task performance (visual sampling and longitudinal control). The model is developed and validated using a dataset from a simplified car-following experiment (N = 40, in both three-dimensional virtual reality and a real instrumented vehicle). The results replicate our previously reported connection between time headway and visual attention. The model reproduces this connection and predicts that it emerges from control of action uncertainty. Implications for traffic psychological models and future developments for psychologically plausible yet computationally rigorous models of full natural task performance are discussed.
Original languageEnglish
Article number180194
JournalRoyal Society Open Science
Volume5
Issue number9
Pages (from-to)1-23
Number of pages23
ISSN2054-5703
DOIs
Publication statusPublished - 5 Sep 2018
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 6162 Cognitive science
  • VISUAL ATTENTION
  • TOP-DOWN CONTROL
  • NATURAL TASK PERFORMANCE
  • DRIVING
  • PREDITIVE PROCESSING
  • COGNITIVE MODELLING
  • BRAKE REACTION-TIMES
  • OPTICAL INFORMATION
  • PERIPHERAL-VISION
  • TO-COLLISION
  • BEHAVIOR
  • RISK
  • SPEED
  • ENVIRONMENT
  • DYNAMICS
  • STRATEGY

Cite this

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title = "A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task",
abstract = "We present a computational model of intermittent visual sampling and locomotor control in a simple yet representative task of a car driver following another vehicle. The model has a number of features that take it beyond the current state of the art in modelling natural tasks, and driving in particular. First, unlike most control theoretical models in vision science and engineering—where control is directly based on observable (optical) variables—actions are based on a temporally enduring internal representation. Second, unlike the more sophisticated engineering driver models based on internal representations, our model explicitly aims to be psychologically plausible, in particular in modelling perceptual processes and their limitations. Third, unlike most psychological models, it is implemented as an actual simulation model capable of full task performance (visual sampling and longitudinal control). The model is developed and validated using a dataset from a simplified car-following experiment (N = 40, in both three-dimensional virtual reality and a real instrumented vehicle). The results replicate our previously reported connection between time headway and visual attention. The model reproduces this connection and predicts that it emerges from control of action uncertainty. Implications for traffic psychological models and future developments for psychologically plausible yet computationally rigorous models of full natural task performance are discussed.",
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author = "Pekkanen, {Jami Joonas Olavi} and Otto Lappi and Paavo Rinkkala and Tuhkanen, {Niko Samuel} and Roosa Frantsi and Summala, {Kari Heikki Ilmari}",
year = "2018",
month = "9",
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language = "English",
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journal = "Royal Society Open Science",
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A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task. / Pekkanen, Jami Joonas Olavi; Lappi, Otto; Rinkkala, Paavo; Tuhkanen, Niko Samuel; Frantsi, Roosa; Summala, Kari Heikki Ilmari.

In: Royal Society Open Science, Vol. 5, No. 9, 180194, 05.09.2018, p. 1-23.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Summala, Kari Heikki Ilmari

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AB - We present a computational model of intermittent visual sampling and locomotor control in a simple yet representative task of a car driver following another vehicle. The model has a number of features that take it beyond the current state of the art in modelling natural tasks, and driving in particular. First, unlike most control theoretical models in vision science and engineering—where control is directly based on observable (optical) variables—actions are based on a temporally enduring internal representation. Second, unlike the more sophisticated engineering driver models based on internal representations, our model explicitly aims to be psychologically plausible, in particular in modelling perceptual processes and their limitations. Third, unlike most psychological models, it is implemented as an actual simulation model capable of full task performance (visual sampling and longitudinal control). The model is developed and validated using a dataset from a simplified car-following experiment (N = 40, in both three-dimensional virtual reality and a real instrumented vehicle). The results replicate our previously reported connection between time headway and visual attention. The model reproduces this connection and predicts that it emerges from control of action uncertainty. Implications for traffic psychological models and future developments for psychologically plausible yet computationally rigorous models of full natural task performance are discussed.

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KW - DYNAMICS

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