Unlocking Federal Grants with a Smarter Parking Classification System
For decades, planners have classified truck parking as either “public” or “private.” This binary view oversimplifies a complex system, overlooking drivers’ diverse needs, planners’ strategic priorities, and the evolving demands of freight. A new framework is needed to guide how we classify and manage truck parking.
The traditional approach lumps facilities into two broad categories:
- Public: Rest areas, service plazas, weigh stations, pull-out areas.
- Private: Full-service truck stops, fuel stations, retail parking lots, undesignated spaces (e.g., highway shoulders).
While ownership matters, this binary ignores critical nuances:
- Amenities: A “private” truck stop with showers and Wi-Fi operates differently from a gas station offering only fuel.
- Capacity: A 50-space travel center serves vastly different demand than a 5-space convenient store lot.
- Safety and Accessibility: Undesignated parking (e.g., highway ramps/shoulders) poses risks but is often a last resort due to shortages.
- Usage Patterns: Drivers prioritize facilities based on location, amenities, and real-time availability—factors unrelated to ownership.
As Nevland et al. (2020) demonstrated, truck parking spans at least 9 distinct types when considering legality, accessibility, and purpose. Yet policymakers still default to oversimplified labels, hindering data-driven decision-making.
Recent research highlights the limitations of the status quo:
- Anderson et al. (2018) identified 11 factors influencing parking challenges, including driver demographics, cargo type, and amenities. For instance, drivers who prioritized amenities like showers or received real-time parking availability data reported fewer difficulties, highlighting the impact of infrastructure and information accessibility on perceived parking adequacy.
- Nevland et al. (2020) emphasized that illegal truck parking often results from systemic gaps in parking infrastructure rather than driver negligence. By classifying truck parking into nine distinct categories, they demonstrated that simple “public” vs. “private” labels are insufficient to explain why drivers resort to unsafe options like highway shoulders. Their findings highlight the need for data-driven policies to address parking shortages and improve truck parking accessibility.
Despite these insights, most state freight plans still treat truck parking as a homogeneous category. This creates two problems:
- Inaccurate Demand Forecasting: A “private” lot at a casino functions differently from one at a warehouse, but both are counted equally.
- Missed Funding Opportunities: Federal grants (e.g., National Highway Freight Program, NHFP) require granular data on facility types, safety, and scalability—details the public-private binary obscures.
A Data-Driven Alternative: Clustering Truck Parking by Function
Our analysis of 11,000+ U.S. truck parking locations used machine learning to group facilities into five functional clusters, based on:
- Parking traits (type, capacity, fees)
- Amenities (food, showers, Wi-Fi)
- Traffic (truck volume, AADT)
The result? Our research team recommends a classification system that reflects real-world usage as follows:
Why This Matters for Planners
A functional classification system isn’t just academic—it’s a tool for actionable solutions:
- Funding Eligibility: Federal programs target safety and electrification gaps. Clustering highlights which sites (e.g., Budget Medium Mixed public rest areas) are strong candidates for grants.
- Capacity Expansion: States can focus on clusters with the biggest payoff. For example, upgrading Budget Small Mixed sites with lighting and security cuts down unsafe roadside parking.
- Public-Private Synergies: Budget Large Full-Service stops sometimes have underused capacity. Incentives like tax breaks or zoning flexibility could unlock more spaces for drivers.
- Driver-Centric Design: Premium Private facilities—with showers, Wi-Fi, and higher security—directly align with driver comfort preferences identified in past surveys.
Conclusion: From Labels to Solutions
The public-private binary is a relic of an era when truck parking was an afterthought. Today, with freight volumes rising and federal funding tied to innovation, planners need a classification system that reflects reality. By adopting a data-driven, functional framework, states can:
- Target investments where demand outstrips supply.
- Leverage partnerships with private operators (e.g., Wyoming’s P3 project).
- Design safer, smarter facilities that drivers actually use.
The goal isn’t just to count parking spots—it’s to build a resilient freight network. And that starts with asking better questions.
More details
- Click here to learn more about the methodology.
- For sample data requests or inquiries, contact our team at: 📧 team@myrigparking.com
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Authored, reviewed, and approved by Troy Choi, Ph.D., P.E. – Transportation Systems Optimization & Engineering Research. Google Scholar (as of 2025): Citations 168 | h-index 4 | i10-index 4