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Article: An improved distance metric for the interpolation of link-based traffic data using kriging:A case study of a large-scale urban road network
Title | An improved distance metric for the interpolation of link-based traffic data using kriging:A case study of a large-scale urban road network |
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Authors | |
Keywords | Distance Metric Geographic Information Systems For Transportation (Gis-T) Isometric Embedding Kriging Traffic Data Interpolation |
Issue Date | 2012 |
Publisher | Taylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp |
Citation | International Journal Of Geographical Information Science, 2012, v. 26 n. 4, p. 667-689 How to Cite? |
Abstract | The interpolation of link-based traffic data is an important topic for transportation researchers and engineers. In recent years the kriging method has been used in traffic data interpolation from the viewpoint of spatial analysis. This method has shown promising results, especially for a large-scale road network. However, existing studies using the Euclidean distance metric, which is widely used in traditional kriging, fail to accurately describe the spatial distance in a road network. In this article we introduce road network distance to describe spatial distance between road links, and we propose an improved distance metric called approximate road network distance (ARND), based on the isometric embedding theory, for solving the problem of the invalid spatial covariance function in kriging caused by the non-Euclidean distance metric. An improved Isomap algorithm is also proposed for obtaining the ARND metric. This study is tested on a large-scale urban road network with sparse road-link travel speeds derived from approximately 1200 'floating cars' (GPS-enabled taxis). Comparison was conducted on both the Euclidean distance metric and the ARND metric. The validation results show that the use of the ARND metric can obtain better interpolation accuracy in different time periods and urban regions with different road network structures. Therefore, we conclude that the improved distance metric has the ability for improving kriging interpolation accuracy for link-based traffic data within real situations, providing more reliable basic traffic data for various traffic applications. © 2012 Copyright Taylor and Francis Group, LLC. |
Persistent Identifier | http://hdl.handle.net/10722/176302 |
ISSN | 2023 Impact Factor: 4.3 2023 SCImago Journal Rankings: 1.436 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
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dc.contributor.author | Zou, H | en_US |
dc.contributor.author | Yue, Y | en_US |
dc.contributor.author | Li, Q | en_US |
dc.contributor.author | Yeh, AGO | en_US |
dc.date.accessioned | 2012-11-26T09:08:18Z | - |
dc.date.available | 2012-11-26T09:08:18Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.citation | International Journal Of Geographical Information Science, 2012, v. 26 n. 4, p. 667-689 | en_US |
dc.identifier.issn | 1365-8816 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/176302 | - |
dc.description.abstract | The interpolation of link-based traffic data is an important topic for transportation researchers and engineers. In recent years the kriging method has been used in traffic data interpolation from the viewpoint of spatial analysis. This method has shown promising results, especially for a large-scale road network. However, existing studies using the Euclidean distance metric, which is widely used in traditional kriging, fail to accurately describe the spatial distance in a road network. In this article we introduce road network distance to describe spatial distance between road links, and we propose an improved distance metric called approximate road network distance (ARND), based on the isometric embedding theory, for solving the problem of the invalid spatial covariance function in kriging caused by the non-Euclidean distance metric. An improved Isomap algorithm is also proposed for obtaining the ARND metric. This study is tested on a large-scale urban road network with sparse road-link travel speeds derived from approximately 1200 'floating cars' (GPS-enabled taxis). Comparison was conducted on both the Euclidean distance metric and the ARND metric. The validation results show that the use of the ARND metric can obtain better interpolation accuracy in different time periods and urban regions with different road network structures. Therefore, we conclude that the improved distance metric has the ability for improving kriging interpolation accuracy for link-based traffic data within real situations, providing more reliable basic traffic data for various traffic applications. © 2012 Copyright Taylor and Francis Group, LLC. | en_US |
dc.language | eng | en_US |
dc.publisher | Taylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp | en_US |
dc.relation.ispartof | International Journal of Geographical Information Science | en_US |
dc.subject | Distance Metric | en_US |
dc.subject | Geographic Information Systems For Transportation (Gis-T) | en_US |
dc.subject | Isometric Embedding | en_US |
dc.subject | Kriging | en_US |
dc.subject | Traffic Data Interpolation | en_US |
dc.title | An improved distance metric for the interpolation of link-based traffic data using kriging:A case study of a large-scale urban road network | en_US |
dc.type | Article | en_US |
dc.identifier.email | Yeh, AGO: hdxugoy@hkucc.hku.hk | en_US |
dc.identifier.authority | Yeh, AGO=rp01033 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1080/13658816.2011.609488 | en_US |
dc.identifier.scopus | eid_2-s2.0-84859412967 | en_US |
dc.identifier.hkuros | 225544 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-84859412967&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 26 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.spage | 667 | en_US |
dc.identifier.epage | 689 | en_US |
dc.identifier.isi | WOS:000301979200005 | - |
dc.publisher.place | United Kingdom | en_US |
dc.identifier.scopusauthorid | Zou, H=35194951800 | en_US |
dc.identifier.scopusauthorid | Yue, Y=35303739000 | en_US |
dc.identifier.scopusauthorid | Li, Q=35173079200 | en_US |
dc.identifier.scopusauthorid | Yeh, AGO=7103069369 | en_US |
dc.identifier.issnl | 1365-8816 | - |