Task-Difficulty Homeostasis in Car Following Models: Experimental Validation Using Self-Paced Visual Occlusion

Jami Pekkanen, Otto Lappi, Teemu Itkonen, Heikki Summala

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Car following (CF) models used in traffic engineering are often criticized for not incorporating “human factors” well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn’t incorporated in the current models.
Original languageEnglish
Article number0169704
JournalPLoS One
Volume12
Issue number1
Number of pages15
ISSN1932-6203
DOIs
Publication statusPublished - 13 Jan 2017
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 6162 Cognitive science
  • cognitive models
  • Driver behaviours
  • Intermittency
  • car following

Cite this

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title = "Task-Difficulty Homeostasis in Car Following Models: Experimental Validation Using Self-Paced Visual Occlusion",
abstract = "Car following (CF) models used in traffic engineering are often criticized for not incorporating “human factors” well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn’t incorporated in the current models.",
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Task-Difficulty Homeostasis in Car Following Models : Experimental Validation Using Self-Paced Visual Occlusion. / Pekkanen, Jami; Lappi, Otto; Itkonen, Teemu; Summala, Heikki.

In: PLoS One, Vol. 12, No. 1, 0169704, 13.01.2017.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Task-Difficulty Homeostasis in Car Following Models

T2 - Experimental Validation Using Self-Paced Visual Occlusion

AU - Pekkanen, Jami

AU - Lappi, Otto

AU - Itkonen, Teemu

AU - Summala, Heikki

PY - 2017/1/13

Y1 - 2017/1/13

N2 - Car following (CF) models used in traffic engineering are often criticized for not incorporating “human factors” well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn’t incorporated in the current models.

AB - Car following (CF) models used in traffic engineering are often criticized for not incorporating “human factors” well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn’t incorporated in the current models.

KW - 6162 Cognitive science

KW - cognitive models

KW - Driver behaviours

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