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SFMTA Municipal Transportation Agency Image: Historic Car number 1 and 162 on Embarcadero




                          Urban Data Challenge
                         Visualizing Transportation Data



               02 | 06 | 2013
               Swissnex
Outline

•    System Overview and Challenges
•    The Datasets
•    Open Government Data
•    What Insights Are We Looking For?




                                         2
Muni Overview
•  SFMTA operates over
   3 million service hours
   annually
•  5 distinct transit modes
   (bus, trolley, cable car,
   light rail, historic streetcar)

•  710,000 daily boardings
   225 million annually
•  4th highest usage in the
   nation (passengers per capita)

                                     3
Street Level Challenges
Transit First City
•  Safe and efficient movement of
   people and goods
•  Promote public transit, bicycle and
   pedestrian travel as attractive
   alternatives
•  Encourage innovative solutions to
   meet public transportation needs
Striving for Reliability




                           6
TEP   Signal Priority   Central Subway




                                         7
Do these policies and projects work?

•  Reliable and faster transit service
•  Reliable: On-time and/or expected headways
•  Reliable: Consistent travel time
•  Faster: Less time to travel
•  Faster: More frequent service at same cost



                                                8
Let’s look at the data for answers
Automatic Vehicle Location (AVL)
Data

•    Time stamp and Lat/long
     every 90 sec or 200 m.
•    Scheduled and actual data.
•    100 percent coverage.


Automatic Passenger Counter
(APC) Data

•    Passenger on/off data.
•    “Dwell time” and traffic delay
     at stops.
•    Scheduled and actual data.
•    Covers 30 percent of bus

                                                9
Travel Time Reliability




                          10
Terminal Departures Performance




                                  12
Geographically Targeted Supervision
Terminal Departures by Time of Day

   Large number of
   late departures




           Early departures
           after 10 p.m.
                              General unreliability
                              during Owl hours
Ridership




            15
Damn it Jim! I’m
    a transit
engineer, not a
 data scientist!
Desired Insights and Visualizations

•  Service
   –  What does the transit map look like by time
      of day?
   –  What does ridership look like by time of
      day?
   –  Where are people coming from and going
      to?


                                                19
Desired Insights and Visualizations
•  Interaction with traffic
    –  Reliability, speed,
       delays
    –  Heartbeat of the City:
       How does the blood
       flow by time of day,
       day of week?



                                          20
Desired Insights and Visualizations

•  Transit Project Benefits




                                        21
Be Creative!
But also help answer the key policy and
         operational questions




       http://www.nytimes.com/interactive/   22
       2010/04/02/nyregion/taxi-map.html?
Go Forth and Visualize!
       Chris Pangilinan @cap_transport
          Felipe Robles @fliprobles
San Francisco Municipal Transportation Agency

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Urban Data Challenge - Christopher A. Pangilinan

  • 1. SFMTA Municipal Transportation Agency Image: Historic Car number 1 and 162 on Embarcadero Urban Data Challenge Visualizing Transportation Data 02 | 06 | 2013 Swissnex
  • 2. Outline •  System Overview and Challenges •  The Datasets •  Open Government Data •  What Insights Are We Looking For? 2
  • 3. Muni Overview •  SFMTA operates over 3 million service hours annually •  5 distinct transit modes (bus, trolley, cable car, light rail, historic streetcar) •  710,000 daily boardings 225 million annually •  4th highest usage in the nation (passengers per capita) 3
  • 5. Transit First City •  Safe and efficient movement of people and goods •  Promote public transit, bicycle and pedestrian travel as attractive alternatives •  Encourage innovative solutions to meet public transportation needs
  • 7. TEP Signal Priority Central Subway 7
  • 8. Do these policies and projects work? •  Reliable and faster transit service •  Reliable: On-time and/or expected headways •  Reliable: Consistent travel time •  Faster: Less time to travel •  Faster: More frequent service at same cost 8
  • 9. Let’s look at the data for answers Automatic Vehicle Location (AVL) Data •  Time stamp and Lat/long every 90 sec or 200 m. •  Scheduled and actual data. •  100 percent coverage. Automatic Passenger Counter (APC) Data •  Passenger on/off data. •  “Dwell time” and traffic delay at stops. •  Scheduled and actual data. •  Covers 30 percent of bus 9
  • 11.
  • 14. Terminal Departures by Time of Day Large number of late departures Early departures after 10 p.m. General unreliability during Owl hours
  • 15. Ridership 15
  • 16.
  • 17. Damn it Jim! I’m a transit engineer, not a data scientist!
  • 18.
  • 19. Desired Insights and Visualizations •  Service –  What does the transit map look like by time of day? –  What does ridership look like by time of day? –  Where are people coming from and going to? 19
  • 20. Desired Insights and Visualizations •  Interaction with traffic –  Reliability, speed, delays –  Heartbeat of the City: How does the blood flow by time of day, day of week? 20
  • 21. Desired Insights and Visualizations •  Transit Project Benefits 21
  • 22. Be Creative! But also help answer the key policy and operational questions http://www.nytimes.com/interactive/ 22 2010/04/02/nyregion/taxi-map.html?
  • 23. Go Forth and Visualize! Chris Pangilinan @cap_transport Felipe Robles @fliprobles San Francisco Municipal Transportation Agency