The influence of anxiety on visual entropy of experienced drivers

Gisele Gotardi, Paulo Schor, John Van Der Kamp, Martina Navarro, Dominic Orth, Geert Savelsbergh, Paula F. Polastri, Raoul Oudejans, Sergio T. Rodrigues

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

67 Downloads (Pure)

Abstract

This study tested the use of entropy to identify changes on behavior of drivers under pressure. Sixteen experienced drivers drove in a simulator wearing a head-mounted eye tracker under low- and high-anxiety conditions. Anxiety was induced by manipulating some psychological factors such as peer-pressure. Fixations transitions between AOIs (lane, speedometer and mirrors) were calculated through first-order transition matrix, transformed to Markov probability matrix and adjusted into the entropy equation. Drivers showed greater state-anxiety scores and higher mean heart rates following manipulation. Under anxiety, drivers showed higher visual entropy, indicating a more random scanning. The randomness implies into a poorer acquisition of information and may indicate an impaired top-down control of attention provoked by anxiety.

Original languageEnglish
Title of host publicationETVIS 2018 Proceedings of the 3rd Workshop on Eye Tracking and Visualization
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
Chapter4
Number of pages4
ISBN (Electronic)9781450357876
DOIs
Publication statusPublished - 15 Jun 2018
Event3rd Workshop on Eye Tracking and Visualization, ETVIS 2018 - Warsaw, Poland
Duration: 14 Jun 201817 Jun 2018

Publication series

NameProceedings - ETVIS 2018: Eye Tracking and Visualization

Conference

Conference3rd Workshop on Eye Tracking and Visualization, ETVIS 2018
CountryPoland
CityWarsaw
Period14/06/1817/06/18

Keywords

  • Anxiety
  • Attentional control theory
  • Fixations
  • Visual entropy

Fingerprint Dive into the research topics of 'The influence of anxiety on visual entropy of experienced drivers'. Together they form a unique fingerprint.

Cite this