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Title: Application of clustering algorithms for spatio-temporal analysis of urban traffic data
Authors: Toshniwal, Durga
Chaturvedi N.
Parida, Manoranjan
Garg A.
Choudhary C.
Choudhary Y.
Published in: Transportation Research Procedia
Proceedings of the World Conference Transport Research, WCTR 2019
Abstract: The large vehicle movement traffic datasets offer a lot of great opportunities for the evolution of new methodologies for the analysis of the transportation system. However, deriving relevant traffic patterns from such a vast amount of historical dataset is challenging. In this paper, several data mining techniques have been applied to obtain more understanding about urban traffic patterns by analyzing hourly and daily variation in urban traffic flow dataset. A model has been developed for the analysis of spatial and temporal patterns in urban traffic data. Model development involves the formulation of algorithms to be applied to the data and choice of various metrics to evaluate the clustering algorithm. Furthermore, these techniques have been applied to the traffic dataset of Aarhus, the second-largest city of Denmark. Finally, results are analyzed to determine the various factors that affect the traffic flow patterns in an urban area.
Citation: Transportation Research Procedia, 2020, 1046- 1059
Issue Date: 2020
Keywords: separated by semicolons
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ISSN: 23521457
Author Scopus IDs: 8683737500
Author Affiliations: Toshniwal, D., Indian Institute of Technology, Roorkee, 247667, India
Chaturvedi, N., Indian Institute of Technology, Roorkee, 247667, India
Parida, M., Indian Institute of Technology, Roorkee, 247667, India
Garg, A., Indian Institute of Technology, Ro
Corresponding Author: Ulengin F.Patil G.R.Ozaydin O.Tavasszy L.Verma A.
Appears in Collections:Conference Publications [CE]

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