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

Research output: Contribution to journalArticleScientificpeer-review

Standard

A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task. / Pekkanen, Jami; Lappi, Otto; Rinkkala, Paavo; Tuhkanen, Samuel; Frantsi, Roosa; Summala, Heikki.

In: Royal Society Open Science, Vol. 5, No. 9, 180194, 01.09.2018.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

APA

Vancouver

Author

Pekkanen, Jami ; Lappi, Otto ; Rinkkala, Paavo ; Tuhkanen, Samuel ; Frantsi, Roosa ; Summala, Heikki. / A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task. In: Royal Society Open Science. 2018 ; Vol. 5, No. 9.

Bibtex - Download

@article{b909fa603b4b475f93d9aeb6864533f8,
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 threedimensional 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.",
keywords = "cognitive modelling, driving, natural task performance, predictive processing, top-down control, visual attention",
author = "Jami Pekkanen and Otto Lappi and Paavo Rinkkala and Samuel Tuhkanen and Roosa Frantsi and Heikki Summala",
year = "2018",
month = "9",
day = "1",
doi = "10.1098/rsos.180194",
language = "English",
volume = "5",
journal = "Royal Society Open Science",
issn = "2054-5703",
number = "9",

}

RIS - Download

TY - JOUR

T1 - A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task

AU - Pekkanen, Jami

AU - Lappi, Otto

AU - Rinkkala, Paavo

AU - Tuhkanen, Samuel

AU - Frantsi, Roosa

AU - Summala, Heikki

PY - 2018/9/1

Y1 - 2018/9/1

N2 - 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 threedimensional 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.

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 threedimensional 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.

KW - cognitive modelling

KW - driving

KW - natural task performance

KW - predictive processing

KW - top-down control

KW - visual attention

UR - http://www.scopus.com/inward/record.url?scp=85054540595&partnerID=8YFLogxK

U2 - 10.1098/rsos.180194

DO - 10.1098/rsos.180194

M3 - Article

VL - 5

JO - Royal Society Open Science

JF - Royal Society Open Science

SN - 2054-5703

IS - 9

M1 - 180194

ER -

ID: 28846640