Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data

David McGookin, Dimitra Gkatzia, Helen Hastie

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

Abstract

Navigation when running is exploratory, characterised by both starting and ending in the same location, and iteratively foraging the environment to find areas with the most suitable running conditions. Runners do not wish to be explicitly directed, or refer to navigation AIDS that cause them to stop running, such as maps. Such undirected navigation is also common in other 'on-foot' scenarios, but how to support it is under-investigated. We contribute a novel method that uses crowd-sourced venue databases to rate a geographical area on its suitability to run in using linear regression. Our regression model is able to accurately predict the suitability of an area to run in (Pearson r=0.74) with a low mean error (RMSE=1.0). We outline how our method can support runners, and can be applied to other undirected navigation scenarios.

Original languageEnglish
Title of host publicationMobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services
PublisherAssociation for Computing Machinery
Pages357-361
Number of pages5
ISBN (Print)9781450336529
DOIs
Publication statusPublished - 24 Aug 2015
Event17th International Conference on Human-Computer Interaction with Mobile Devices and Services 2015 - Copenhagen, Denmark
Duration: 24 Aug 201527 Aug 2015

Conference

Conference17th International Conference on Human-Computer Interaction with Mobile Devices and Services 2015
Abbreviated titleMobileHCI 2015
CountryDenmark
CityCopenhagen
Period24/08/1527/08/15

Keywords

  • Exploratory navigation
  • Foursquare
  • Machine learning
  • Open street map
  • Pedestrian navigation
  • Regression analysis
  • Running

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Computer Networks and Communications
  • Human-Computer Interaction

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  • Cite this

    McGookin, D., Gkatzia, D., & Hastie, H. (2015). Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data. In MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services (pp. 357-361). Association for Computing Machinery. https://doi.org/10.1145/2785830.2785879