Issue No. 05 - May (2014 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.89
Bin Yang , Dept. of Comput. Sci., Aarhus Univ., Aarhus, Denmark
Manohar Kaul , Dept. of Comput. Sci., Aarhus Univ., Aarhus, Denmark
Christian S. Jensen , Dept. of Comput. Sci., Aalborg Univ., Aalborg, Denmark
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.
vehicle routing, graph theory, regression analysis, road traffic, search engines, traffic engineering computing,travel time, complete weight annotation, road networks, vehicle routing, weighted-graph models, transportation networks, GHG emissions, GPS trajectory data, travel cost based weights, associated ground-truth travel cost, regression problem, road network topology, weighted PageRank values, directional adjacency,Roads, Global Positioning System, Vectors, Vehicles, Fuels, Estimation, Markov processes,Correlation and regression analysis, Information Technology and Systems, Database Management, Database Applications, Spatial databases and GIS, Database Management, Database Applications, Data mining, Mathematics of Computing, Probability and Statistics,correlation and regression analysis, Spatial databases and GIS
Bin Yang, Manohar Kaul, Christian S. Jensen, "Using Incomplete Information for Complete Weight Annotation of Road Networks", IEEE Transactions on Knowledge & Data Engineering, vol. 26, no. , pp. 1267-1279, May 2014, doi:10.1109/TKDE.2013.89