THESIS
2011
x, 41 p. : ill. ; 30 cm
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 traje...[
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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.
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