Visual analysis of route diversity

He Liu, Yuan Gao, Lu Lu, Siyuan Liu, Huamin Qu, Lionel M. Ni

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

101 Scopus citations

Abstract

Route suggestion is an important feature of GPS navigation systems. Recently, Microsoft T-drive has been enabled to suggest routes chosen by experienced taxi drivers for given source/destination pairs in given time periods, which often take less time than the routes calculated according to distance. However, in real environments, taxi drivers may use different routes to reach the same destination, which we call route diversity. In this paper we first propose a trajectory visualization method that examines the regions where the diversity exists and then develop several novel visualization techniques to display the high dimensional attributes and statistics associated with different routes to help users analyze diversity patterns. Our techniques have been applied to the real trajectory data of thousands of taxis and some interesting findings about route diversity have been obtained. We further demonstrate that our system can be used not only to suggest better routes for drivers but also to analyze traffic bottlenecks for transportation management.

Original languageEnglish (US)
Title of host publicationVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings
Pages171-180
Number of pages10
DOIs
StatePublished - 2011
Event2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011 - Providence, RI, United States
Duration: Oct 23 2011Oct 28 2011

Publication series

NameVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings

Other

Other2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011
Country/TerritoryUnited States
CityProvidence, RI
Period10/23/1110/28/11

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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