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• W2890972190 abstract "In this paper we consider aggregation technique to reduce the complexity of large-scale traffic network. In particular, we consider the city of Grenoble and show that, by clustering adjacent sections based on a similarity of speed condition, it is possible to cut down the complexity of the network without loosing crucial and intrinsic information. To this end, we consider travel time computation as a metric of comparison between the original graph and the reduced one: for each cluster we define four attributes (average speed, primary and secondary length and heading) and show that, in case of an aggregation rate of 95%, these attributes are sufficient in order to maintain the travel time error below the 25%." @default.
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• W2890972190 date "2018-10-01" @default.
• W2890972190 modified "2023-10-03" @default.
• W2890972190 title "Aggregation and travel time calculation over large scale traffic networks: An empiric study on the Grenoble City" @default.
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• W2890972190 doi "https://doi.org/10.1016/j.trc.2018.07.033" @default.
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