San Francisco Municipal Transportation Agency’s (SFMTA) experience managing a large-scale demand-responsive parking system.
Between 2011 and 2013 the San Francisco Municipal Transportation Agency (SFMTA) implemented the SFpark pilot project, which used in-ground sensors and new parking meters to collect real-time data so parking prices could be adjusted based on occupancy. The sensors had a short operational life. However, all parking meters were upgraded to those collecting payment data. Thus, while occupancy data is no longer available, payment data from all parking meters is still available. Sensor and meter data collected during the SFpark pilot were used to develop a sensor-independent rate adjustment (SIRA) model that estimates parking occupancy using meter payment data, which enables demand-responsive pricing policies without large-scale sensor installations.
Recalibrate parking rate adjustment models when changes to parking policies and regulations may affect non-payment behavior. A major assumption that can impact the accuracy of the model is non-payment, or the difference between the payment rate and the occupancy rate. Non-payment may be influenced through parking policies and practices including:
- legal forms of meter non-payment (e.g., disabled placards)
- time limits
- payment methods
- parking enforcement strategies
- enforcement fines
Changes in these factors would need to be significant and sustained to lead a change in behavior and non-payment. Cities looking to implement demand-responsive pricing using a SIRA model should consider these factors as well as how other parking policies and practices may affect non-payment.