: In the state-of-the-art of structural engineering the actions for design or assessment of bridges should derive from a probabilistic (i.e., frequentist) characterization of the loads. Data from weigh-in-motion (WIM) systems can inform stochastic models for traffic loads. However, WIM is not widespread, and data of this kind are scarce in the literature and often not recent. Due to structural safety reasons, the 52 km long A3 highway in Italy, connecting the cities of Naples and Salerno, has been equipped with a WIM system which has been operational since the beginning of 2021. The system's measurements of each vehicle transiting over the WIM devices, impede overloads on the many bridges featured in the transportation infrastructure. By the time of this writing the WIM system has seen one year of uninterrupted operation, collecting more than thirty-six million datapoints in the meantime. This short paper presents and discusses these WIM measurements, deriving the empirical distributions of traffic loads and making the original data available for further research and applications.

Empirical distributions of traffic loads from one year of weigh-in-motion data

Iervolino, Iunio;
2023-01-01

Abstract

: In the state-of-the-art of structural engineering the actions for design or assessment of bridges should derive from a probabilistic (i.e., frequentist) characterization of the loads. Data from weigh-in-motion (WIM) systems can inform stochastic models for traffic loads. However, WIM is not widespread, and data of this kind are scarce in the literature and often not recent. Due to structural safety reasons, the 52 km long A3 highway in Italy, connecting the cities of Naples and Salerno, has been equipped with a WIM system which has been operational since the beginning of 2021. The system's measurements of each vehicle transiting over the WIM devices, impede overloads on the many bridges featured in the transportation infrastructure. By the time of this writing the WIM system has seen one year of uninterrupted operation, collecting more than thirty-six million datapoints in the meantime. This short paper presents and discusses these WIM measurements, deriving the empirical distributions of traffic loads and making the original data available for further research and applications.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12076/17221
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