Probabilistic-based methods for extreme traffic loads mapping to assist bridge portfolio management

From Synthetic Vehicle Load Observations to Bridge Criticality and Beyond.

Vehicle load investigation is crucial for assessing the reliability of existing road infrastructure, given the potential threats posed by extreme traffic loads, including risks to road transport operations and the integrity of pavements and bridges. The most reliable source for gathering massive vehicle load information is Weigh-in-Motion (WIM) technology. WIM systems play a pivotal role in collecting data on vehicular loads, individual axle loads, vehicle types, and axle counts, holding significant relevance in engineering for the design of new bridges and the reliability assessment of existing structures. However, the inherent high costs associated with WIM systems have limited their adoption, leading many regions to rely on the use of less sophisticated traffic counters (LSTC). The drawbacks of such alternatives, including inaccurate axle counting during high truck volumes and the absence of vehicle weighing, must be considered when assessing the reliability of road infrastructure at a network level.

One of the first steps in the reliability assessment of road infrastructure at the network level is the identification of critical locations within the network. This involves, for example, identifying critical road locations due to extreme gross vehicle weights and critical bridge locations due to extreme load effects. The goal is to generate optimal bridge intervention programs taking into account these performance indicators to minimize costs. Therefore, in cases where WIM data is unavailable (or limited), the computation of synthetic WIM observations becomes crucial. Synthetic WIM observations should approximate statistical characteristics (including dependencies). of real traffic data. ns and safety risks for society…