Mapping hazardous locations on a road network due to extreme gross vehicle weights

Gross vehicle weights (GVW) have been estimated using Gaussian Copula-based Bayesian networks (GCBN) for 1777 traffic counting stations situated along
the fifteen major highway corridors in Mexico.

The map below displays the calculated GVW with a 50-year return period (GVW-50) and the GVW with a 1000-year return period (GVW-1000) for each counting station.
This map makes it easier to identify hazardous locations caused by GVW and can be a valuable resource for developing maintenance strategies for existing roads and bridges.

General Information:

• Traffic counting station: Includes details about the number, federal entity, name, year of measurements, the Annual Average Daily Truck Traffic (AADTT),
  the proportion of traffic flow per vehicle type, the estimated GVW, and the major highway corridor number (MHC).
• Gaussian Copula-based Bayesian networks: Provides a graphical representation of the site-specific GCBN, usually named NPBN.
  Each row of the GCBN represents one vehicle type and each node represents the distribution of individual axle loads per vehicle type.

This information will be displayed in a pop-up window when you select a particular counting station on the map.

The scientific publication supporting this map can be found at https://doi.org/10.1016/j.ress.2023.109698