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| Seuring, Stefan |
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| Nor Azizi, S. |
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| Pato, Margarida Vaz |
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| Kölker, Katrin |
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| Huber, Oliver |
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| Király, Tamás |
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| Spengler, Thomas Stefan |
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| Al-Ammar, Essam A. |
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| Dargahi, Fatemeh |
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| Mota, Rui |
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| Mazalan, Nurul Aliah Amirah |
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| Macharis, Cathy | Brussels |
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| Arunasari, Yova Tri |
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| Nunez, Alfredo | Delft |
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| Bouhorma, Mohammed |
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| Bonato, Matteo |
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| Fitriani, Ira |
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| Autor Correspondente Coelho, Sílvia. |
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| Pond, Stephen |
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| Okwara, Ukoha Kalu |
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| Toufigh, Vahid |
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| Campisi, Tiziana | Enna |
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| Ermolieva, Tatiana |
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| Sánchez-Cambronero, Santos |
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| Agzamov, Akhror |
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Malekjafarian, Abdollah
University College Dublin
in Cooperation with on an Cooperation-Score of 37%
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Publications (13/13 displayed)
- 2024Predicting the duration of motorway incidents using machine learningcitations
- 2023Methodological Framework for Assessing and Strengthening the Resistance of Railway Critical Infrastructure Elements
- 2022Indirect Monitoring of Frequencies of a Multiple Span Bridge Using Data Collected from an Instrumented Train: A Field Case Studycitations
- 2021Measuring traffic load on Forth Road Suspension Bridge using Weigh-InMotion and image data
- 2020Identifying Critical Clusters of Traffic-Loading Events in Recurrent Congested Conditions on a Long-Span Road Bridgecitations
- 2019Estimation of traffic load effects on Forth Road Bridge using camera measurements
- 2019Evaluation of the extreme traffic load effects on the Forth Road Bridge using image analysis of traffic datacitations
- 2018Estimation of traffic load effects on Forth Road Bridge using camera measurements
- 2017Damage detection using curvatures obtained from vehicle measurementscitations
- 2017On the use of a passing vehicle for the estimation of bridge mode shapescitations
- 2017On the use of drive-by measurement for indirect bridge monitoring
- 2017Application of empirical mode decomposition to drive-by bridge damage detectioncitations
- 2016A mode shape-based damage detection approach using laser measurement from a vehicle crossing a simply supported bridgecitations
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document
Measuring traffic load on Forth Road Suspension Bridge using Weigh-InMotion and image data
Abstract
This paper uses a camera and image analysis to complement Weigh-In-Motion (WIM) data on a long-span bridge and determine characteristic maximum load effects in congested traffic situations. The camera system measures vehicle positions and hence car/truck mix and inter-vehicle gaps, all key data for long-span bridge loading. It also measures vehicle lengths and approximates weights from the lengths, using data from a WIM system adjacent to the bridge. The approach is shown to give good accuracy and to be in sensitivity to inaccuracies in the weights of individual vehicles. The high-resolution camera captured image data on the Forth Road Bridge in Scotland (Figure 1) at1 second intervals over a five-month period. Standard image processing approaches are applied to extract the lengths of the vehicles from the images (Figure 2).Calibration factors are used to convert the lengths in the images from pixels to metres and to correct for perspective. Free-flowing traffic captured by the camera is compared with the same traffic recorded by the on-site WIM system to calibrate and confirm the accuracy of the calibration process. A year of data from the WIM system is used to establish the correlations between vehicle lengths and weights and hence to provide estimates of weights for vehicles identified in the images. The approach is used to gather bridge traffic load information including car/truck mix and intervehicle gaps. Bridge load effect data are fitted to Extreme Value statistical distributions to calculate characteristic maximum values (Figure 3). For fully jammed conditions, results are shown to be sensitive to the frequency of traffic jams on the bridge.
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