Monitoring vehicles with permits and that are illegally overweight on bridges using Weigh-In-Motion (WIM) devices: A case study from Brescia

Ventura, Roberto; Barabino, Benedetto; Vetturi, David; Maternini, Giulio

doi:10.1016/j.cstp.2023.101023

Cited by 7 publications

(5 citation statements)

References 30 publications

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“…The Brescia metropolitan area houses many businesses involved in processing iron and steel goods, manufacturing heavy and high-density metal products, and features several quarries extracting stone materials for construction work. Consequently, there is a substantial demand for heavy lorry transportation, which subsequently affects the road network ( [6], [7]). A bridge along Brescia's South Ring Road was selected in collaboration with the local Road Authority (RA), i.e., the Provincia of Brescia.…”

Section: A Research Contextmentioning

confidence: 99%

See 1 more Smart Citation

Traffic Hazards on Main Road’s Bridges: Real-Time Estimating and Managing the Overload Risk

Ventura,

Maternini,

Barabino

2024

IEEE Trans. Intell. Transport. Syst.

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The risk associated with extreme traffic loads on bridges has seldom been explored, with State-of-the-art evaluation methods being time-consuming and unsuitable for fast risk management. Traditional risk management advocates optimizing offline bridge maintenance plans. In contrast, novel approaches that can assess and manage this risk live through Intelligent Transportation Systems (ITSs) are lacking. This study addresses these gaps with a three-block framework. It utilizes Weigh-In-Motion (WIM) systems for collecting bridge-specific traffic load data, develops a probabilistic Risk Prediction Model for estimating the frequency and severity of overloading events drawing on current Structural Design Codes (SDCs), and simulates an ITS-based architecture for implementing management actions. The framework was tested on 2.5M+ WIM raw data records gathered from the ring road of Brescia, Italy. Results showed that bridge design loads were overcome more frequently than SDCs prescriptions, and violations of the Traffic Code mass limit significantly affected risk predictions. These findings underscore the need for increased attention when issuing permits for extremely overweighted vehicles and encourage enforcement strategies implemented by ITS-based architectures for real-time risk management.Index Terms-Bridge overload risk, bridge risk prediction models, weigh-in-motion, real-time bridge management strategies, traffic load hazard. I. INTRODUCTIONB RIDGES are among the most vulnerable elements of road networks because they may have structural issues that could compromise their use or, worst case, cause a collapse [1]. The whole transportation system is impacted by a bridge closure, being a negative event that lengthens user travel times, stops commodities from reaching their destinations and results in additional congestion [2]. After hydraulic actions, vehicular traffic is the primary element that affects bridge

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Section: A Research Contextmentioning

confidence: 99%

“…Extremely heavy trucks can be subdivided into two categories: Permits (PMTs) and Illegally Overweighted Vehicles (IOVs) ( [6], [7], [8]). PMTs have a Gross Vehicular Mass (GVM) that exceeds the restrictions outlined in the Traffic Code (TC).…”

mentioning

confidence: 99%

Traffic Hazards on Main Road’s Bridges: Real-Time Estimating and Managing the Overload Risk

Ventura,

Maternini,

Barabino

2024

IEEE Trans. Intell. Transport. Syst.

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show abstract

“…At the best fit, the permutation feature importance of each severity predictor (PFI f ) was computed according to eqn. (5). The results are shown in the Appendix (Table A2).…”

Section: Block 3: Machine Learning Modelmentioning

confidence: 99%

Prediction of the Severity of Exceeding Design Traffic Loads on Highway Bridges

Ventura,

Barabino,

Maternini

2023

Preprint

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“…WIM systems provide a dynamic measurement of vehicle mass, allowing for enforcement measures against overloaded trucks and the prevention of roadway and bridge damage [ 5 ]. Additionally, these systems can collect information on the total amount of traffic that passes on any given roadway, the date, and time that it passes, as well as the speed and the size of the vehicles, the number of axles on those vehicles, the mass acting on each axle, the type of axles, and the interaxle distances [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of the severity of exceeding design traffic loads on highway bridges

Ventura,

Barabino,

Maternini

2024

Heliyon

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Monitoring vehicles with permits and that are illegally overweight on bridges using Weigh-In-Motion (WIM) devices: A case study from Brescia

Cited by 7 publications

References 30 publications

Traffic Hazards on Main Road’s Bridges: Real-Time Estimating and Managing the Overload Risk

Traffic Hazards on Main Road’s Bridges: Real-Time Estimating and Managing the Overload Risk

Prediction of the Severity of Exceeding Design Traffic Loads on Highway Bridges

Prediction of the severity of exceeding design traffic loads on highway bridges

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