Lesson

Recalibrate parking rate adjustment models when changes to parking policies and regulations may affect non-payment behavior.

San Francisco Municipal Transportation Agency’s (SFMTA) experience managing a large-scale demand-responsive parking system.


11/13/2015
San Francisco; California; United States


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Lesson Learned

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.


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Source

Demand-Responsive Pricing on the Cheap: Estimating Parking Occupancy Using Meter Payment Data

Author: Demisch, Alex

Published By: Transportation Research Board

Source Date: 11/13/2015

URL: http://docs.trb.org/prp/16-1656.pdf

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Lesson Contacts

Lesson Analyst:

Janet Fraser
Noblis
304-848-3924
janet.fraser@noblis.org


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States

California

Countries

United States

Focus Areas

None defined

Goal Areas

Efficiency

Keywords

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Lesson ID: 2016-00737