Identifying proper scales on digital maps for in-vehicle navigation systems

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

4 Scopus citations

Abstract

Current commercial mobile navigation systems often use a pre-determined scale selection schema without considering differences in spatial complexity of locations. To identify what map scales people may need and what spatial features make relevant maps stand out, we conducted an experiment on subjective map selection in a route planning task between two cities in the United States. Our results suggest that the distribution of selected maps is fairly concentrated on those maps that contain spatial information about both the origin and the destination, the current location and the destination, and the transition between different important roads in a route. These results suggest that the choice of map scales should not follow a preset scale rule for diverse locations, and instead, it should be adaptive to the complexity of local roads and decision-making processes.

Original languageEnglish (US)
Title of host publicationUniversal Access in Human-Computer Interaction
Subtitle of host publicationApplications and Services - 5th International Conference, UAHCI 2009 - Held as Part of HCI International 2009, Proceedings
Pages262-270
Number of pages9
EditionPART 3
DOIs
StatePublished - 2009
Event5th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2009. Held as Part of HCI International 2009 - San Diego, CA, United States
Duration: Jul 19 2009Jul 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5616 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2009. Held as Part of HCI International 2009
Country/TerritoryUnited States
CitySan Diego, CA
Period7/19/097/24/09

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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