A Mobility Impedance Index for Data-Driven National Bridge Preservation Prioritization

Bridge management systems primarily prioritize structural condition, while pavement management systems focus on roadway performance. Neither provides a unified measure of the potential for bridges to impede traffic movement by jointly considering infrastructure condition and traffic demand. This separation limits the ability of stakeholders to identify bridges where preservation investments may yield the greatest mobility benefits across a national transportation network. This study develops a mobility impedance index (MII) by integrating pavement roughness, bridge deck condition, current traffic demand, and projected traffic growth into a single composite measure. A transparent and transferrable data-integration and prioritization methodology was developed to spatially integrate the Highway Performance Monitoring System (HPMS) and National Bridge Inventory (NBI), producing a national analytical dataset of 79,595 open, unrestricted mainline NHS bridges in the contiguous United States. The index was evaluated using distributional analysis, local Getis-Ord hotspot analysis, sensitivity testing, and temporal comparability assessment. The MII exhibited a well-behaved generalized normal distribution and identified 20,621 bridges as statistically significant local hotspots, concentrated primarily within major metropolitan regions and high-demand transportation corridors. Sensitivity analyses demonstrated that the proposed MII is robust, with bridge-rank correlations ranging from 0.807 to 0.965 across the alternative specification scenarios and hotspot-set similarities ranging from 0.446 to 0.801. Restricting the analysis to bridges whose component observation years were within three years produced virtually identical prioritization results (Spearman ρ = 0.999), confirming that temporal differences among the component datasets have negligible influence on bridge rankings. The proposed MII provides transportation agencies with a nationally scalable data-driven decision-support method for network-level bridge prioritization that complements existing bridge and pavement management practices by identifying bridges and regions where preservation investments are likely to provide the greatest mobility benefits and support more sustainable allocation of limited infrastructure preservation resources.