Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridge
Source abstract
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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Research context
OpenAlex topics: Infrastructure Maintenance and Monitoring · Structural Engineering and Vibration Analysis · Traffic control and management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Amey Consulting, Forth Road Bridge, Administration Building, South Queensferry EH30 9QZ, UK
School of Natural and Built Environment, Queen’s University Belfast, David Keir Building, Belfast BT9 5AG, UK
Civil Infrastructure Technologies for Resilience and Safety, University of Central Florida, Orlando, FL 32816-2450, USA
Funding
Science Foundation Ireland
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