Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/96536
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Logistics and Maritime Studies | en_US |
dc.creator | Xing, J | en_US |
dc.creator | Wu, W | en_US |
dc.creator | Cheng, Q | en_US |
dc.creator | Liu, R | en_US |
dc.date.accessioned | 2022-12-07T02:55:20Z | - |
dc.date.available | 2022-12-07T02:55:20Z | - |
dc.identifier.issn | 0378-4371 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/96536 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | en_US |
dc.rights | The following publication Xing, J., Wu, W., Cheng, Q., & Liu, R. (2022). Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights. Physica A: Statistical Mechanics and its Applications, 595, 127079 is available at https://doi.org/10.1016/j.physa.2022.127079. | en_US |
dc.subject | Data fusion | en_US |
dc.subject | Missing traffic state estimation | en_US |
dc.subject | Multi-source data application | en_US |
dc.subject | Systematic review | en_US |
dc.subject | Urban road network | en_US |
dc.title | Traffic state estimation of urban road networks by multi-source data fusion : review and new insights | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 595 | en_US |
dc.identifier.doi | 10.1016/j.physa.2022.127079 | en_US |
dcterms.abstract | Accurate traffic state (i.e., flow, speed, density, etc.) on an urban road network is important information for urban traffic control and management strategies. However, due to the limitation of detector installation cost, it is difficult to obtain accurate traffic states through detectors in the whole urban road network with limited detector equipment. In this paper, we review the studies that focus on the missing traffic state estimation problem, especially for the traffic state estimation on the segments without detectors. We provide a way to summarize for readers who have an interest in the different modelling and application of missing traffic state estimation. We first divide the existing studies into three categories: estimation under different missing scenarios, estimation with multi-source data, estimation by fusing different detector types. Then, we summary some existing challenges by the different missing scenarios, data applications, and methodologies. Finally, this work also discusses some future research directions. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Physica A. Statistical mechanics and its applications, 1 June 2022, v. 595, 127079 | en_US |
dcterms.isPartOf | Physica A. Statistical mechanics and its applications | en_US |
dcterms.issued | 2022-06-01 | - |
dc.identifier.eissn | 1873-2119 | en_US |
dc.identifier.artn | 127079 | en_US |
dc.description.validate | 202212 bckw | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1-s2.0-S037843712200125X-main.pdf | 3.04 MB | Adobe PDF | View/Open |
Page views
58
Last Week
3
3
Last month
Citations as of May 12, 2024
Downloads
64
Citations as of May 12, 2024
SCOPUSTM
Citations
31
Citations as of May 17, 2024
WEB OF SCIENCETM
Citations
22
Citations as of May 16, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.