Washington, D.C.: Integrating Real-Time Parking Data

Washington, D.C. at a Glance

Location: Washington, D.C.

Program: parkDC Penn Quarter/Chinatown

Deployment: 482 Fybr in-ground parking sensors deployed

Applications: Real-time parking availability, occupancy analytics and demand-responsive parking

The Challenge

In Washington, D.C.’s busy Penn Quarter and Chinatown neighborhoods, the District Department of Transportation (DDOT) wanted to make parking easier to find while reducing circling, congestion and inefficient use of curb space.

DDOT’s parkDC program tested how real-time occupancy information could be combined with payment, enforcement and other parking data to better understand demand, communicate parking availability and support demand-responsive pricing.

Deploying Real-Time Occupancy Detection

Fybr provided in-ground parking sensors and real-time, space-level occupancy data that fed into the broader parking-management system.

Fybr was not the only occupancy technology used by parkDC. DDOT evaluated two in-ground sensor providers as well as camera-based approaches. After assessing the two sensor providers, DDOT determined that both were acceptable and divided the pilot area’s sensor deployment between them.

Integrating Real-Time Data Into ParkDC

Fybr’s role extended beyond detecting whether individual parking spaces were occupied. Real-time occupancy data from the Fybr network was integrated into the broader ParkDC system, where parking information could be combined with other data and used to support parking management and customer information.

DDOT used ParkDC to provide motorists with information about parking availability and rates while using parking-demand data to inform management of the curb.

This demonstrated an important capability for a city’s parking ecosystem: real-time, space-level occupancy data could operate as an integrated data layer rather than a standalone sensor system.

Combining Direct Occupancy Detection With Other Parking Data

One of parkDC’s most important findings was that cities could combine direct occupancy detection with data already generated by their parking systems.

DDOT developed what it called an “asset-lite” approach, combining observations from sensors and cameras with payment transactions, citations, historical occupancy patterns and other information. A peer-reviewed Transportation Research Record paper documented the program’s data-fusion strategy.

Importantly, DDOT found that payment data was not a complete substitute for direct occupancy detection. Placard use, free government parking and motorists leaving before their paid time expired all created differences between payment activity and actual occupancy.

DDOT concluded that payment information could reduce the amount of occupancy technology required, but could not fully replace direct occupancy detection.

ParkDC Final Report — U.S. DOT National Transportation Library

That distinction remains important for modern parking and curb management: transactions show payment activity; occupancy detection provides direct information about whether a vehicle is actually present.

DDOT-Measured Results

Fybr was one component of a broader parkDC program involving multiple occupancy technologies, data sources, demand-responsive pricing and customer information. The overall program results therefore cannot be attributed to Fybr alone.

DDOT used parking-demand information to adjust meter rates by location and time of day. In lower-demand portions of the pilot area, occupancy increased 12% following pricing and time-limit changes. Parking customers also reported spending seven minutes less searching for a space.

U.S. DOT subsequently highlighted both results in its evaluation of parkDC.

U.S. DOT ITS Deployment Evaluation: parkDC

Following the pilot, DDOT continued demand-based pricing in Penn Quarter and Chinatown.

DDOT: Penn Quarter/Chinatown Pilot Results

From Pilot Deployment to Long-Term Operation

Fybr’s involvement in Washington extended well beyond the initial parkDC pilot. Fybr installed 400 sensors in 2016 and expanded the deployment with another 82 sensors in 2019.

Fybr continued providing sensor services until September 2023, more than seven years after the initial deployment.

Washington demonstrated how direct occupancy detection could become part of a broader, interoperable parking system and remain there over the long term. The larger lesson remains relevant today: combine direct knowledge of what is happening at the curb with the other parking data already available to a city.

Sources

District Department of Transportation: parkDC Penn Quarter/Chinatown Pricing Pilot Final Report

DDOT’s comprehensive evaluation documents the program’s occupancy-detection strategy, use of multiple technologies, asset-lite architecture, demand-responsive pricing and measured outcomes.

ParkDC Final Report — U.S. DOT National Transportation Library

District Department of Transportation: Parking Occupancy Sensor GIS Layer

DDOT Parking Occupancy Sensor GIS Layer

District Department of Transportation: Penn Quarter/Chinatown Pilot Results

DDOT’s official announcement summarizes the pilot’s results and continuation of demand-based pricing.

DDOT Pilot Results Announcement

Transportation Research Record: Asset-Lite Parking: Big Data Analytics in Development of Sustainable Smart Parking Solutions in Washington, D.C.

The peer-reviewed paper documents parkDC’s approach to combining occupancy detection with other parking data.

Transportation Research Record: Asset-Lite Parking

U.S. Department of Transportation: ITS Deployment Evaluation

U.S. DOT documents measured parkDC outcomes, including the 12% increase in occupancy in lower-demand areas and seven-minute reduction in parking-search time.