Research · Truck parking classification
Classify truck parking by function, not just ownership
“Public” and “private” are too blunt for today’s truck parking system. A functional classification better reflects how sites operate, what drivers need, and which facilities are the strongest candidates for safety, electrification, and freight funding.
Truck parking locations analyzed.
Functional groups recommended.
Parking categories identified by Nevland et al.
Key takeaways
Ownership alone does not explain how a site serves drivers
- Key takeawayCapacity, amenities, accessibility, and traffic context matter as much as who owns the lot.
- Why it mattersA functional classification improves demand forecasting, supports stronger grant applications, and targets upgrades where they reduce unsafe parking the most.
- What we recommendGroup facilities by function using parking traits, amenities, and traffic conditions instead of the public-private split alone.
The status quo
Why the public-private split falls short
Traditional inventories group facilities into two buckets. That keeps ownership visible, but it hides the operational differences that matter for planning.
Public
Rest areas, service plazas, weigh stations, and pull-out areas are counted together even though they differ in size, access, and amenities.
Private
Full-service truck stops, fuel stations, retail lots, and undesignated spaces are grouped together despite serving very different needs.
- Amenities are not comparableA full-service truck stop with showers and Wi-Fi does not function like a fuel-only site or a small convenience-store lot.
- Capacity is not comparableA 50-space travel center and a 5-space lot may both count as “private,” but they serve very different levels of demand.
- Safety and legality differHighway shoulders and ramps can land in the same broad class as legitimate sites even though they reflect system failure and higher risk.
- Usage is driven by functionDrivers choose sites based on location, amenities, and availability, not on who owns the property.
Prior research
What prior research already shows
Recent studies show that truck parking problems are shaped by much more than ownership.
Anderson et al. (2018)
Identified multiple factors behind parking difficulty, including driver characteristics, cargo type, information availability, and amenities such as showers.
Drivers who received parking information or had access to better amenities reported fewer parking difficulties.
Nevland et al. (2020)
Showed that illegal truck parking is often a symptom of infrastructure gaps, not simple driver negligence.
By identifying nine truck parking types, they demonstrated that “public” versus “private” does not explain why drivers end up on unsafe options such as highway shoulders.
Bottom line: treating truck parking as one homogeneous category misses both demand differences and funding opportunities.
Planning impact
Two planning problems the binary system creates
- Inaccurate demand forecastingA casino lot, a warehouse lot, and a premium full-service stop may all count as “private,” even though they attract different drivers, dwell times, and capacity.
- Missed funding opportunitiesPrograms such as the National Highway Freight Program reward specific safety, capacity, resiliency, and implementation logic. That case is harder to make when all parking sits in coarse categories.
A data-driven alternative
Clustering by function
We analyzed 11,000+ U.S. truck parking locations and grouped them into five functional clusters using operational characteristics instead of ownership alone.
Inputs used for clustering
- Parking traits: type, capacity, and fees
- Amenities: food, showers, and Wi-Fi
- Traffic context: truck volume and AADT
The result better reflects how sites are actually used and where they fit within a freight network.
For planners
Why this matters for planners
A functional classification is not just descriptive. It helps states act.
- Funding eligibilityClustering shows which sites best align with safety, resilience, and electrification goals in competitive grant programs.
- Capacity expansionStates can focus on clusters where small upgrades, such as lighting or security, could reduce unsafe roadside parking.
- Public-private coordinationSome larger private sites may have underused potential that incentives, zoning flexibility, or partnership models could unlock.
- Driver-centered designHigher-amenity clusters match the preferences drivers express in surveys, especially around comfort and security.
In practice
How a smarter classification supports better projects
Target investment
Use clusters to identify high-need public rest areas and mixed-use sites where demand is strong and capacity shortfalls are most harmful.
Improve safety
Prioritize clusters tied to undesignated parking so that infrastructure spending directly reduces shoulder and ramp parking.
Strengthen grant applications
Functional data gives agencies a clearer story about need, site suitability, and expected benefits, which competitive programs reward.
Conclusion
From labels to solutions
The public-private split is a legacy shortcut. Today’s freight network needs a classification that reflects how parking actually works.
- Target investments where demand most clearly exceeds supply.
- Support partnerships with private operators where expansion is feasible.
- Design safer, smarter facilities that drivers will actually use.
The goal is not just to count spaces. It is to build a more resilient freight network, and that starts with better categories.
Authored, reviewed, and approved by Troy Choi, Ph.D., P.E. Transportation Systems Optimization and Engineering Research.
See the classification on your state’s inventory
Every Trucking Lab dataset carries the functional cluster for each facility, ready for freight plans and grant narratives.
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