Managing parking in San Francisco requires innovative solutions, and the San Francisco Municipal Transportation Agency (SFMTA) partnered with DIXON to implement the Rapid LPR Tool. This advanced system transforms raw License Plate Recognition (LPR) data into actionable insights, delivering precise analysis of parking occupancy, turnover, and enforcement trends.

In 2021, DIXON piloted the Rapid LPR Tool with SFMTA to test the accuracy and viability of using vehicle-mounted LPR technology to collect parking data. By comparing LPR results with dashboard-camera footage, the pilot demonstrated the effectiveness of translating raw license plate information into reliable occupancy and turnover analysis. This also provided SFMTA with an opportunity to audit its Genetec LPR cameras, resulting in technology improvements and substantial cost reparations for its parking enforcement program.

Following the pilot’s success, DIXON replaced SFMTA’s Sensor Independent Rate Adjustment (SIRA) model with the Rapid LPR Tool, automating data collection for all paid parking locations citywide. The system now integrates with Genetec’s database, processes LPR data daily, and publishes results to a user-friendly web dashboard, with strict privacy measures ensuring anonymized license plate data.
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Key Achievements

• Enhanced Data Collection: Supported over 80 LPR-equipped vehicles and a dedicated data team, collecting consistent and reliable data.
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• Automated Data Integration: Developed an API allowing SFMTA to pull occupancy and turnover data directly into the City’s database, enabling demand-based rate adjustments.
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• Expanded Capabilities: Extended the tool to analyze Residential Permit Parking (RPP) areas, aiding decisions on expanding RPP and paid parking programs.
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• Cost-Effective Insights: Enabled mobile LPR to replace fixed sensors, allowing flexible data collection anywhere, anytime, without heavy hardware investments.
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DIXON’s innovative approach has transformed San Francisco’s demand-based parking strategies, improving operational efficiency and user experience while proving the power of mobile LPR for data-driven decision-making.