CLW 2014: The fourth workshop on cognitive load and in-vehicle human-machine interaction

Andrew L. Kun, W. Thomas Miller, Peter Froehlich, Ivan Tashev, Paul A. Green, Shamsi Iqbal, Bryan Reimer, Thomas M. Gable, Peter A. Heeman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Interactions with in-vehicle electronic devices can interfere with the primary task of driving and increase crash risk. Interactions with in-vehicle interfaces draw upon visual, manipulative and cognitive resources, with this workshop focusing on cognitive resources for which measurement processes are less well known or established. This workshop will focus on two methods of measuring cognitive load, the Decision Response Time Task and collecting eye fixation data. The workshop will describe and demonstrate how they are collected, and discuss how the resulting data are reduced and analyzed. The focus will be on practical aspects of collecting and analyzing data using these methods, not on reporting research results.

Original languageEnglish (US)
Title of host publicationAutomotiveUI 2014 - 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, in Cooperation with ACM SIGCHI - Adjunct Proceedings
PublisherAssociation for Computing Machinery
Pages52-55
Number of pages4
ISBN (Electronic)9781450307253
DOIs
StatePublished - Sep 17 2014
Event6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2014 - Seattle, United States
Duration: Sep 17 2014Sep 19 2014

Publication series

NameAutomotiveUI 2014 - 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, in Cooperation with ACM SIGCHI - Adjunct Proceedings

Other

Other6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2014
Country/TerritoryUnited States
CitySeattle
Period9/17/149/19/14

Keywords

  • Cognitive load
  • Driving
  • Estimation
  • Management

ASJC Scopus subject areas

  • Automotive Engineering
  • Artificial Intelligence

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