Washington, DC, just released the results from its four-year pilot program, parkDC, which applied dynamic pricing for on-street parking in Penn Quarter and Chinatown. Based on its success, the city is now working to expand the program beyond the pilot area. The program, which built upon the earlier success of those like San Francisco’s SFpark, achieved similar results with fewer resources.
To lower the program’s cost, the city developed an “asset-lite” approach to data collection, which relied on strategically placed cameras and in-ground sensors, along with networked meters, enforcement data, and pay-by-cell transaction records. This approach took several key steps: 1) demarcating on-street spaces; 2) focusing on block-level probabilities instead of precise space availability; and 3) fusing all of the available data sources to minimize the number of sensors needed.