Name
Abstract | ||
|---|---|---|
We are witnessing increasing interests in the effective use of road networks. For example, to enable effective vehicle routing, weighted-graph models of transportation networks are used, where the weight of an edge captures some cost associated with traversing the edge, e.g., greenhouse gas (GHG) emissions or travel time. It is a precondition to using a graph model for routing that all edges have weights. Weights that capture travel times and GHG emissions can be extracted from GPS trajectory data collected from the network. However, GPS trajectory data typically lack the coverage needed to assign weights to all edges. This paper formulates and addresses the problem of annotating all edges in a road network with travel cost based weights from a set of trips in the network that cover only a small fraction of the edges, each with an associated ground-truth travel cost. A general framework is proposed to solve the problem. Specifically, the problem is modeled as a regression problem and solved by minimizing a judiciously designed objective function that takes into account the topology of the road network. In particular, the use of weighted PageRank values of edges is explored for assigning appropriate weights to all edges, and the property of directional adjacency of edges is also taken into account to assign weights. Empirical studies with weights capturing travel time and GHG emissions on two road networks (Skagen, Denmark, and North Jutland, Denmark) offer insight into the design properties of the proposed techniques and offer evidence that the techniques are effective. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TKDE.2013.89 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
travel time,database applications,weighted pagerank values,regression problem,spatial databases and gis,database management,vehicle routing,associated ground-truth travel cost,traffic engineering computing,regression analysis,information technology and systems,gps trajectory data,road network topology,road networks,mathematics of computing,probability and statistics,correlation and regression analysis,transportation networks,travel cost based weights,directional adjacency,data mining,graph theory,road traffic,complete weight annotation,weighted-graph models,search engines,ghg emissions,global positioning system,markov processes,estimation,vectors | Adjacency list,Data mining,PageRank,Probability and statistics,Vehicle routing problem,Computer science,Precondition,Artificial intelligence,Empirical research,Complete information,Machine learning,Traverse | Journal |
Volume | Issue | ISSN |
26 | 5 | 1041-4347 |
Citations | PageRank | References |
33 | 1.52 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Yang | 1 | 706 | 34.93 |
| Manohar Kaul | 2 | 185 | 13.76 |
| Christian S. Jensen | 3 | 10651 | 1129.45 |