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Popular Route Planning with Travel CostEstimationHuiping Liu, Cheqing Jin, Aoyin Zhou Institute for Data Science and Engineering, Software Engineering Institute,East China Normal University, China 1
AgendaIntroductionOverview Popular Traverse Graph ConstructionTravel Cost ModellingRoute PlanningExperimentsConclusion2
IntroductionShortest or fastest path is not enough in route planningABFinding the Popular Route with Accurate Travel Cost Estimation3
Existing WorkYuan J, Zheng Y, Zhang C, et al. T-drive: driving directions based on taxi trajectories. (SIGSPATIAL 2010)Based on road network informationPractical fastest path is not always popularWang Y, Zheng Y, Xue Y. Travel time estimation of a path using sparse trajectories. (KDD 2014)Travel time estimation of a given pathCan not be directly used in route planning4
Overview5
Popular Traverse Graph ConstructionA popular route has a support ≥ τ (predefined) Road network information is not always available.We try to construct a popular traverse graph G=(V,E) from trajectories, where V is the set of popular locations and E is the set of popular routes between locations.6
Popular Traverse Graph ConstructionPoints clusteringA popular route has a support ≥ τ (predefined) Road network information is not always available.We try to construct a popular traverse graph G=(V,E) from trajectories, where V is the set of popular locations and E is the set of popular routes between locations.7
Popular Traverse Graph ConstructionPoints clusteringTrajectory clustering(τ = 2)A popular route has a support ≥ τ (predefined) Road network information is not always available.We try to construct a popular traverse graph G=(V,E) from trajectories, where V is the set of popular locations and E is the set of popular routes between locations.8
Modeling travel cost on popular routeThe travel cost on each route varies at different timeWe mining the travel cost pattern at different time slots for an accurate time cost estimationA good partition for
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