Paper Info
Title
Stochastic skyline route planning under time-varying uncertainty
Abstract
Different uses of a road network call for the consideration of different travel costs: in route planning, travel time and distance are typically considered, and green house gas (GHG) emissions are increasingly being considered. Further, travel costs such as travel time and GHG emissions are time-dependent and uncertain. To support such uses, we propose techniques that enable the construction of a multi-cost, time-dependent, uncertain graph (MTUG) model of a road network based on GPS data from vehicles that traversed the road network. Based on the MTUG, we define stochastic skyline routes that consider multiple costs and time-dependent uncertainty, and we propose efficient algorithms to retrieve stochastic skyline routes for a given source-destination pair and a start time. Empirical studies with three road networks in Denmark and a substantial GPS data set offer insight into the design properties of the MTUG and the efficiency of the stochastic skyline routing algorithms.
Year
DOI
Venue
2014
10.1109/ICDE.2014.6816646
ICDE
Keywords
Field
DocType
travel time,global positioning system,stochastic skyline route planning,time-varying uncertainty,traffic engineering computing,global positioning systems,denmark,travel distance,gps data,mtug model,travel costs,road network,multicost time-dependent uncertain graph model,source-destination pair,directed graphs,data handling,road traffic,greenhouse gas emission,ghg emissions,uncertainty,stochastic processes,random variables,routing
Skyline,Graph,Data mining,Random variable,Route planning,Simulation,Computer science,Operations research,Stochastic process,Global Positioning System,Empirical research,Greenhouse gas
Conference
ISSN
Citations 
PageRank 
1084-4627
46
1.39
References 
Authors
14
5
Name
Order
Citations
PageRank
Bin Yang170634.93
Chenjuan Guo230116.81
Christian S. Jensen3106511129.45
Manohar Kaul418513.76
Shuo Shang538017.17