the sfpark pilot: using data to make cities better

Post on 16-Jul-2015

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Part 1: Background & overview

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What is parking like in San Francisco?

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Demonstrating a new approach to parking

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Part 2: Preparations

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Parking census

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Inventory/asset management

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Framing and messaging

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Identity and brand management

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Part 3: Implementation

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Coin and card meters

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Parking sensors

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Pricing at parking meters and lots• Demand responsive to find lowest possible prices • Gradual and periodic changes: $0.25 up or down every 4-6 weeks • Time of day pricing (vary by block + weekday/end)

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Demand responsive rate adjustments

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Real-time information

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Pricing at SFpark parking garages

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Wayfinding signs

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Variable message signs

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Part 4: Operation

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Investment in data management/analytical tools

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Acquire + understand + clean + structure data

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Part 5: Evaluation

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Automatic data• Supply data (census, asset management, street closures)• Parking data (from sensors, meters, and citations)• Garage data (usage by hour)• Travel demand data (roadway sensors, highways PEMS, BART, Muni) • Muni data (travel time data from APCs)• Parking tax• Sales tax• Safety (SWITIRS collision data)• Exogenous (fuel price, CPI, unemployment, precipitation)

Manual data• Parking search time• Double parking and disabled placard• Intercept surveys (professional survey firm)

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How did rates change?

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Was it easier to park?

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Was it easier to park?

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Secondary benefits we expected• Easier to pay and avoid citations• Easier to find a parking space • Parking spaces better utilized• Less circling• Less vehicle miles travelled• Decreased greenhouse gas emissions• Decreased double parking• Improve Muni speed• Supported economic vitality and safety

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Easier to pay and avoid citations

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Easier to find a parking space

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Decreased vehicle miles travelled

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Decreased greenhouse gas emissions

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Decreased double parking

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Improved Muni speed

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Supported economic vitality and safety

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Additional findings

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Part 5: What’s next & lessons learned

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What’s next• Monitor first rate change using only meter payment data• Finish upgrading meters citywide• Disseminate overview, evaluation, and technical manual • Develop proposal for expanding the SFpark approach to

remaining SFMTA meters, lots, and garages

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Lessons learned• What worked well

– Large investment in communication and customer experience – Transparent, rules-based, and data-driven process– Data sharing + openness– Clear goals and policies

• What was challenging– This approach is very IT intensive– Parking sensors are a nascent product/industry– Culture change takes time

• Recognizing parking management as tool • Emphasizing availability rather than turnover

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Learn more

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Kathryn Doherty-Chapman

For more information on SFpark contact:Steph NelsonSteph.nelson@sfmta.comSFMTA

Thank you

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