Modeling route complexity ratings

H. Schwartz-Chassidim, J. Meyer, Y. Parmet

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

Abstract

We develop a predictive model of the perceived complexity of routes in road maps, taking into account the properties of the road, the task and the map display. Sixty subjects ranked the complexity of 120 routes on scales between 0 and 10. Half of them described the route verbally before rating it. Subjects also completed a questionnaire about the influence of different variables on the route complexity. A linear regression model explained much of the dependent variable's variance (R2 = 0.63). The number of turns and rotations, the perceived density of the map and route length were significant predictors. Describing the route before rating it may lower its apparent complexity. Subjects' assessments of the contribution of different variables to perceptions of route complexity differed from the actual contribution of the variables in the models. The model of perceived route complexity can be used to design road maps that minimize the user's cognitive load.

Original languageEnglish
Title of host publication2014 International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
PublisherHuman Factors an Ergonomics Society Inc.
Pages1696-1700
Number of pages5
ISBN (Electronic)9780945289456
DOIs
StatePublished - 1 Jan 2014
Event58th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014 - Chicago, United States
Duration: 27 Oct 201431 Oct 2014

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Volume2014-January
ISSN (Print)1071-1813

Conference

Conference58th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
Country/TerritoryUnited States
CityChicago
Period27/10/1431/10/14

Keywords

  • Digital road map
  • Model development
  • Pereived complexity
  • Route
  • Scale

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