Welcome
Interactive Map
Analysis
Purpose: This prototype presents a strategic facility-location analysis for North Carolina's interstate truck parking network. The objective is to identify where new rest areas and truck stops should be added along the major corridors (I-26, I-40, I-77, I-85, I-95) to reduce unserved peak-hour parking demand within an investment budget.
The dashboard combines an interactive map of corridors and facilities with a set of analytical views summarizing current system performance, the trade-off between cost and unmet demand, and the optimization model's preferred facility mix.
The Interactive Map shows corridor segments colored by base-case unmet demand and toggleable layers for existing facilities, candidate sites, and new facilities selected by the model at p = 10, 20, 30, 40, 50. The Analysis tab provides a system snapshot, demand patterns by interstate, capacity-utilization histograms, the detour-threshold sensitivity, a capacity-expansion alternative, and the optimal facility mix by p.
Demand Estimation. Peak-hour truck parking demand is estimated for each corridor segment using the FHWA Jason's Law method (FHWA 2002), scaled by AADTT (from NCDOT Traffic Volume Maps), peak seasonal factor (1.15), peak-hour factor, and class-specific facility-preference factors. Demand is decomposed across four driver classes: short-haul vs long-haul, crossed with rest-area vs truck-stop preference.
Candidate Sites. 123 NCDOT-owned parcels were shortlisted from 520 state-owned parcels in NC OneMap. Selection criteria: lying within a 10-mile buffer of I-26, I-77, I-85, or I-95, with capacity ≥ 10 spaces.
Demand Assignment. A two-stage system-optimal assignment is solved: stage 1 maximizes the total number of trucks parked subject to capacity and detour-distance constraints; stage 2, among all assignments achieving that maximum, minimizes total detour distance. Two detour thresholds are reported: 5-mile (stricter) and 10-mile (more permissive).
Facility Location Optimization. A Mixed-Integer Linear Program (MILP) parameterized by p (number of new facilities). For each p from 1 to 50, the model chooses which candidates to open and as which type (rest area or truck stop), subject to demand-balance, capacity, detour, and type-compatibility constraints (rest-area classes can only be served by rest areas; truck-stop classes only by truck stops). Solver: CPLEX.
Cost Specifications. Unit costs are taken from the NCDOT Phase II Truck Parking Study (Cambridge Systematics, Table 3.9):
| Description | Unit | Cost |
|---|---|---|
| Concrete Pavement with Curbs | Per Space | $75,000 |
| Asphalt Pavement, no Curbs | Per Space | $48,000 |
| Gravel Surface | Per Space | $37,000 |
| Vault Toilets | Per Site | $60,000 |
| Lighting | Per Space | $1,400 |
| Fencing (60" chain link) | Per Space | $2,500 |
The per-facility cost is built up as a fixed site cost plus a capacity-dependent pavement cost. For a new truck stop, the fixed component is $60,000 (vault toilets) + $1,400 (lighting) + $2,500 (fencing) = $63,900, and the capacity-dependent component is $75,000 × capacity (concrete pavement with curbs), giving a total of $63,900 + ($75,000 × capacity). For a new rest area, the fixed component is $1,400 (lighting) and the capacity-dependent component is $37,000 × capacity (gravel surface), giving a total of $1,400 + ($37,000 × capacity).
Lighting and fencing are modeled as fixed per-facility line items rather than scaled per space, on the assumption of a single shared installation per site. Existing-facility expansion is costed at the added capacity multiplied by the relevant per-space pavement rate.
Further reference: FHWA Truck Parking Development Handbook (HOP-22-027).
For more details, please read our full report here.
This research was supported by the Center for Rural and Regional Connected Communities (CR2C2), a Regional University Transportation Center funded by the United States Department of Transportation (USDOT). The primary design for the tool was developed by Komal Gulati and Venktesh Pandey, with refinement from the project 3-1 team.
Disclaimer: The views and accuracy of the information presented belong to the authors alone. The United States Department of Transportation assumes no liability for the contents or use thereof.
Komal Gulati (PhD Student, Electrical & Computer Engineering, NC A&T), Dr. Venktesh Pandey (Assistant Professor, Civil, Architectural, & Environmental Engineering, NC A&T).