Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge

E. Alexandra Micu; Eugene J. O'Brien; Abdollah Malekjafarian; Ross McKinstray; Ewan Angus; Myra Lydon; F. Necati Catbas

doi:10.3390/APP10165423

Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge

E. Alexandra Micu^*, Eugene J. O'Brien, Abdollah Malekjafarian, Ross McKinstray, Ewan Angus, Myra Lydon, F. Necati Catbas

^*Corresponding author for this work

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Abstract

This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.

Original language	English
Article number	5423
Number of pages	14
Journal	Applied Sciences (Switzerland)
Volume	10
Issue number	16
DOIs	https://doi.org/10.3390/APP10165423
Publication status	Published - 05 Aug 2020

Bibliographical note

Funding Information:
This research was funded by Science Foundation Ireland under US/Ireland programme, grant 14/US/I3033. The authors gratefully acknowledge Science Foundation Ireland for supporting this research under US/Ireland programme grant 14/US/I3033.

Publisher Copyright:
© 2020 by the authors.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

Bridge
Cluster
Congestion
Dendrogram
Flow
Image
Loading
Long-span
Non-recurrent
Recurrent
Suspension
Traffic

ASJC Scopus subject areas

Materials Science(all)
Instrumentation
Engineering(all)
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes

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10.3390/APP10165423Licence: CC BY

Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge
Copyright 2020 the authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Final published version, 5.41 MBLicence: CC BY

Cite this

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title = "Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge",

abstract = "This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.",

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author = "Micu, {E. Alexandra} and O'Brien, {Eugene J.} and Abdollah Malekjafarian and Ross McKinstray and Ewan Angus and Myra Lydon and Catbas, {F. Necati}",

note = "Funding Information: This research was funded by Science Foundation Ireland under US/Ireland programme, grant 14/US/I3033. The authors gratefully acknowledge Science Foundation Ireland for supporting this research under US/Ireland programme grant 14/US/I3033. Publisher Copyright: {\textcopyright} 2020 by the authors. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

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AU - McKinstray, Ross

AU - Angus, Ewan

AU - Lydon, Myra

AU - Catbas, F. Necati

N1 - Funding Information: This research was funded by Science Foundation Ireland under US/Ireland programme, grant 14/US/I3033. The authors gratefully acknowledge Science Foundation Ireland for supporting this research under US/Ireland programme grant 14/US/I3033. Publisher Copyright: © 2020 by the authors. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/8/5

Y1 - 2020/8/5

N2 - This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.

AB - This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.

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KW - Dendrogram

KW - Flow

KW - Image

KW - Loading

KW - Long-span

KW - Non-recurrent

KW - Recurrent

KW - Suspension

KW - Traffic

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Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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