Smart Parking Strategy for Freight Infrastructure Planning in North Carolina 

 To address critical truck parking shortages along major freight corridors in North Carolina, we developed a comprehensive solution that integrates spatial analytics, behavioral modeling, and mathematical optimization. This framework estimates demand at the highway segment level for four driver classes (short- and long-haul with rest area or truck stop preferences), using FHWA parameters and North Carolina-specific truck traffic data. A linear programming model was applied to quantify unmet demand, guiding a multi-criteria prioritization of over 127 candidate locations based on truck influx, crash severity, accessibility (detour time), and estimated parking capacity. These metrics were normalized and aggregated into composite scores to support site ranking.

An iterative, budget-aware spatial prioritization algorithm was implemented, combining composite scores, demand reduction efficiency, and infrastructure compatibility. Under a $175 million budget scenario, the algorithm selected 14 optimal truck stop locations, reducing statewide unmet demand by 51%. An expanded scenario demonstrated further benefits with 50 facility selections and a 61% demand reduction. Results highlight long-haul truck stop demand as the primary unmet need (Class 4, 76%) and validate the framework’s ability to match infrastructure development with operational freight needs. The solution supports data-driven investment in rural and urban corridors alike, enabling strategic public-private coordination and long-term resilience of North Carolina’s freight network.

Link to the tool: TBD

Related Publication: TBD