Journal
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Volume 13, Issue 1, Pages 110-119Publisher
ELSEVIER
DOI: 10.1016/j.jag.2010.07.003
Keywords
Path-finding; Road network; Hierarchy; Taxi trajectory; Navigation system
Categories
Funding
- National Natural Science Foundation of China [40830530, 60872132]
- National Basic Research Program of China [2006CB705500]
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Optimal paths computed by conventional path-planning algorithms are usually not optimal since realistic traffic information and local road network characteristics are not considered. We present a new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories. The approach consists of three steps. First, routes are recovered from original taxi trajectories. Second, an experiential road hierarchy is constructed using travel frequency and speed information for road segments. Third, experiential optimal paths are planned based on the experiential road hierarchy. Compared with conventional path-planning methods, the proposed method provides better experiential optimal path identification. Experiments demonstrate that the travel time is less for these experiential paths than for paths planned by conventional methods. Results obtained for a case study in the city of Wuhan, China, demonstrate that experiential optimal paths can be flexibly obtained in different time intervals, particularly during peak hours. (C) 2010 Elsevier B.V. All rights reserved.
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