Finding directions to a good GPS system: A comparative analysis and development of a predictive model

James Landy, Tatiana Lopez, Nkemjika Ndee, Pimpisa Predaswad, Eyobin Lozano, Patricia Morreale

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

Abstract

GPS devices have become commonplace today, almost as common as cell phones, especially for the developed and emerging economies. In this research paper, the development of a predictive model for selecting a GPS system for use based on the analysis of the interface design is described. The research presents subjective data from user interaction surveys, and objective data using the Keystroke Level Model (KLM). After comparison, inferences or predictions are made based on the analysis of available data. The research makes valid contributions to the GPS interface design field, and the GPS market. A higher level of accuracy can be achieved with data from a larger user survey group, and use of additional models, and an automated tool such as CogTool.

Original languageEnglish
Title of host publicationHuman-Computer Interaction
Subtitle of host publicationApplications and Services - 16th International Conference, HCI International 2014, Proceedings
PublisherSpringer Verlag
Pages454-465
Number of pages12
EditionPART 3
ISBN (Print)9783319072265
DOIs
StatePublished - 2014
Event16th International Conference on Human-Computer Interaction: Applications and Services, HCI International 2014 - Heraklion, Crete, Greece
Duration: 22 Jun 201427 Jun 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume8512 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Human-Computer Interaction: Applications and Services, HCI International 2014
Country/TerritoryGreece
CityHeraklion, Crete
Period22/06/1427/06/14

Keywords

  • DeLorme Street Atlas
  • Garmin
  • GoogleMaps
  • GPS
  • KLM
  • Magellan
  • predictive model
  • TomTom
  • user survey

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