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Center for Urban Transportation Research | University of South Florida
GTFS-realtime v2.0
Sean J. Barbeau, Ph.D.
Principal Mobile Software Architect for R&D
Center for Urban Transportation Research
University of South Florida
2
Why real-time transit info?
• Real-time information (RTI) has many benefits
– Shorter perceived wait time [1][8]
– Shorter actual wait time[1]
– Lowers learning curve for new riders [2]
– Increased feeling of safety (e.g., at night) [5][6]
– Improved perception of agency[8]
– Increased ridership[3][7]
• Improve the rider experience without increasing
vehicle frequency
• Emerging analytics tools are powered by this data
[1] Kari Edison Watkins, Brian Ferris, Alan Borning, G. Scott Rutherford, and David Layton (2011), "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders," Transportation Research Part A: Policy and Practice, Vol. 45 pp. 839-848.
[2] C. Cluett, S. Bregman, and J. Richman (2003). "Customer Preferences for Transit ATIS," Federal Transit Administration. Available at http://ntl.bts.gov/lib/jpodocs/repts_te/13935/13935.pdf#sthash.jwn5Oltr.dpuf
[3] Lei Tang and Piyushimita Thakuriah (2012), "Ridership effects of real-time bus information system: A case study in the City of Chicago," Transportation Research Part C: Emerging Technologies, Vol. 22 pp. 146-161.
[4] Aaron Steinfeld and John Zimmerman, "Interviews with transit riders in San Francisco and Seattle," ed, 2010.
[5] Brian Ferris, Kari Watkins, and Alan Borning (2010), "OneBusAway: results from providing real-time arrival information for public transit," in Proceedings of the 28th International CHI Conference on Human Factors in Computing Systems, Atlanta, Georgia, USA, pp. 1807-1816.
[6] A. Gooze, K. Watkins, and A. Borning (2013), "Benefits of Real-Time Information and the Impacts of Data Accuracy on the Rider Experience," in Transportation Research Board 92nd Annual Meeting, Washington, D.C., January 13, 2013.
[7] Brakewood, Macfarlane and Watkins (2015). The Impact of Real-Time Information on Bus Ridership in New York City. Transportation Research Part C: Emerging Technologies, Volume 53, pp. 59-7
[8] Brakewood, Barbeau, and Watkins (2014). An experiment evaluating the impacts of real-time transit information on bus riders in Tampa, Florida,, Transportation Research Part A, Volume 69, pp. 409-422.
Tony Kurdzuk/The Star-Ledger
3
• GTFS-realtime is becoming de facto standard
– Over 50 agencies now have GTFS-realtime feeds!
4
Quality is important!
• In one study, 9% of riders said they took the
bus less often due to errors in RTI[9]
• GTFS-realtime v2.0 will help agencies produce
better quality RTI
[9] A. Gooze, K. Watkins, and A. Borning (2013), “Benefits of Real-Time Information and the Impacts of Data Accuracy on the Rider
Experience,” in Transportation Research Board 92nd Annual Meeting, Washington, D.C., January 13, 2013.
5
WHAT’S WRONG WITH
GTFS-REALTIME V1.0?
6
Problem with GTFS-realtime v1.0
• A LOT of optional fields – 56 out of 63 (89%)
– Quirk of Protocol Buffer docs (for details see
http://bit.ly/gtfs-realtime-2)
• Leads to sub-optimal feeds
– Poor data quality
– Bad rider experience
– Inaccurate analytics – garbage in, garbage out
7
Example 1 – Vehicle Position
• All timestamps are
optional
• When was position
calculated?
8
Example 2 – Loop route
• stop_sequence field is optional
• Is 15 minute delay before or after stop_id B?
stop_id = B
stop_id = A
Delay?
9
57
42
0
10
20
30
40
50
60
Total feeds
processed
Feeds with errors
Industry-wide
GTFS-realtime v1.0
Validation Results
https://github.com/CUTR-at-USF/gtfs-realtime-validator
• ~75% of feeds we
analyzed had errors
10
GTFS-REALTIME V2.0
Clarifying what’s really optional
11
GTFS-realtime v2.0
• Defines new transit-specific requirements
• Each field is labeled as either:
– Required
– Optional
– Conditionally required
• See Description field for when this field is required
12
13
GTFS-REALTIME
VALIDATOR
Quick analysis of feeds
14
GTFS-realtime Validator
• Test your v1 and v2 feeds for errors
– Live demo - http://transittools.forest.usf.edu/
– Open-source at https://github.com/CUTR-at-
USF/gtfs-realtime-validator
15
GTFS-rt Validator – View data & errors
16
What’s next?
• Agencies
– In RFPs, request that all AVL vendors provide GTFS-
realtime v2.0 feeds, and use validator
• Github is official new home of GTFS/GTFS-realtime
specs - https://github.com/google/transit
• Community
– Create GTFS-realtime Best Practices
• “Warning” from GTFS-realtime validator[1]
• Proposals without unanimous agreement
– Clarify more GTFS-realtime gray areas
• See list at http://bit.ly/gtfs-realtime-open-topics
[1] http://bit.ly/gtfs-realtime-rules
17
Thanks!
Funding from:
@sjbarbeau
linkedin.com/in/seanbarbeauSean J. Barbeau, Ph.D.
barbeau@cutr.usf.edu
813.974.7208
More on GTFS-realtime v2.0 - http://bit.ly/gtfs-realtime-2
18
19
WHY SO MANY OPTIONAL
FIELDS?
20
GTFS-rt uses Protocol Buffer (PB) format
• gtfs-realtime.proto PB file defines elements to exchange
PB config file
21
Protocol Buffers save space
• Compressed binary is around 6 times smaller
than plain text
22
PB required = transit required
• v1.0 - Optional/required for Cardinality field
values were copied from .proto file
23
0 5 10 15 20 25 30 35 40
E011 - GTFS-rt stop_id does not exist in GTFS data
E022 - Sequential stop_time_update times are not increasing
E045 - GTFS-rt stop_time_update stop_sequence and stop_id do not
match GTFS
E012 - Header timestamp should be greater than or equal to all other
timestamps
E023 - trip start_time does not match first GTFS arrival_time
E041 - trip doesn't have any stop_time_updates
E001 - Not in POSIX time
W009 - schedule_relationship not populated
W001 - timestamps not populated
W002 - vehicle_id not populated
W008 - Header timestamp is older than 65 seconds
W004 - vehicle speed is unrealistic
Most Frequent Errors and Warnings in GTFS-realtime feeds
Number of feeds with error/warning

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GTFS-realtime v2.0

  • 1. Center for Urban Transportation Research | University of South Florida GTFS-realtime v2.0 Sean J. Barbeau, Ph.D. Principal Mobile Software Architect for R&D Center for Urban Transportation Research University of South Florida
  • 2. 2 Why real-time transit info? • Real-time information (RTI) has many benefits – Shorter perceived wait time [1][8] – Shorter actual wait time[1] – Lowers learning curve for new riders [2] – Increased feeling of safety (e.g., at night) [5][6] – Improved perception of agency[8] – Increased ridership[3][7] • Improve the rider experience without increasing vehicle frequency • Emerging analytics tools are powered by this data [1] Kari Edison Watkins, Brian Ferris, Alan Borning, G. Scott Rutherford, and David Layton (2011), "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders," Transportation Research Part A: Policy and Practice, Vol. 45 pp. 839-848. [2] C. Cluett, S. Bregman, and J. Richman (2003). "Customer Preferences for Transit ATIS," Federal Transit Administration. Available at http://ntl.bts.gov/lib/jpodocs/repts_te/13935/13935.pdf#sthash.jwn5Oltr.dpuf [3] Lei Tang and Piyushimita Thakuriah (2012), "Ridership effects of real-time bus information system: A case study in the City of Chicago," Transportation Research Part C: Emerging Technologies, Vol. 22 pp. 146-161. [4] Aaron Steinfeld and John Zimmerman, "Interviews with transit riders in San Francisco and Seattle," ed, 2010. [5] Brian Ferris, Kari Watkins, and Alan Borning (2010), "OneBusAway: results from providing real-time arrival information for public transit," in Proceedings of the 28th International CHI Conference on Human Factors in Computing Systems, Atlanta, Georgia, USA, pp. 1807-1816. [6] A. Gooze, K. Watkins, and A. Borning (2013), "Benefits of Real-Time Information and the Impacts of Data Accuracy on the Rider Experience," in Transportation Research Board 92nd Annual Meeting, Washington, D.C., January 13, 2013. [7] Brakewood, Macfarlane and Watkins (2015). The Impact of Real-Time Information on Bus Ridership in New York City. Transportation Research Part C: Emerging Technologies, Volume 53, pp. 59-7 [8] Brakewood, Barbeau, and Watkins (2014). An experiment evaluating the impacts of real-time transit information on bus riders in Tampa, Florida,, Transportation Research Part A, Volume 69, pp. 409-422. Tony Kurdzuk/The Star-Ledger
  • 3. 3 • GTFS-realtime is becoming de facto standard – Over 50 agencies now have GTFS-realtime feeds!
  • 4. 4 Quality is important! • In one study, 9% of riders said they took the bus less often due to errors in RTI[9] • GTFS-realtime v2.0 will help agencies produce better quality RTI [9] A. Gooze, K. Watkins, and A. Borning (2013), “Benefits of Real-Time Information and the Impacts of Data Accuracy on the Rider Experience,” in Transportation Research Board 92nd Annual Meeting, Washington, D.C., January 13, 2013.
  • 6. 6 Problem with GTFS-realtime v1.0 • A LOT of optional fields – 56 out of 63 (89%) – Quirk of Protocol Buffer docs (for details see http://bit.ly/gtfs-realtime-2) • Leads to sub-optimal feeds – Poor data quality – Bad rider experience – Inaccurate analytics – garbage in, garbage out
  • 7. 7 Example 1 – Vehicle Position • All timestamps are optional • When was position calculated?
  • 8. 8 Example 2 – Loop route • stop_sequence field is optional • Is 15 minute delay before or after stop_id B? stop_id = B stop_id = A Delay?
  • 9. 9 57 42 0 10 20 30 40 50 60 Total feeds processed Feeds with errors Industry-wide GTFS-realtime v1.0 Validation Results https://github.com/CUTR-at-USF/gtfs-realtime-validator • ~75% of feeds we analyzed had errors
  • 11. 11 GTFS-realtime v2.0 • Defines new transit-specific requirements • Each field is labeled as either: – Required – Optional – Conditionally required • See Description field for when this field is required
  • 12. 12
  • 14. 14 GTFS-realtime Validator • Test your v1 and v2 feeds for errors – Live demo - http://transittools.forest.usf.edu/ – Open-source at https://github.com/CUTR-at- USF/gtfs-realtime-validator
  • 15. 15 GTFS-rt Validator – View data & errors
  • 16. 16 What’s next? • Agencies – In RFPs, request that all AVL vendors provide GTFS- realtime v2.0 feeds, and use validator • Github is official new home of GTFS/GTFS-realtime specs - https://github.com/google/transit • Community – Create GTFS-realtime Best Practices • “Warning” from GTFS-realtime validator[1] • Proposals without unanimous agreement – Clarify more GTFS-realtime gray areas • See list at http://bit.ly/gtfs-realtime-open-topics [1] http://bit.ly/gtfs-realtime-rules
  • 17. 17 Thanks! Funding from: @sjbarbeau linkedin.com/in/seanbarbeauSean J. Barbeau, Ph.D. barbeau@cutr.usf.edu 813.974.7208 More on GTFS-realtime v2.0 - http://bit.ly/gtfs-realtime-2
  • 18. 18
  • 19. 19 WHY SO MANY OPTIONAL FIELDS?
  • 20. 20 GTFS-rt uses Protocol Buffer (PB) format • gtfs-realtime.proto PB file defines elements to exchange PB config file
  • 21. 21 Protocol Buffers save space • Compressed binary is around 6 times smaller than plain text
  • 22. 22 PB required = transit required • v1.0 - Optional/required for Cardinality field values were copied from .proto file
  • 23. 23 0 5 10 15 20 25 30 35 40 E011 - GTFS-rt stop_id does not exist in GTFS data E022 - Sequential stop_time_update times are not increasing E045 - GTFS-rt stop_time_update stop_sequence and stop_id do not match GTFS E012 - Header timestamp should be greater than or equal to all other timestamps E023 - trip start_time does not match first GTFS arrival_time E041 - trip doesn't have any stop_time_updates E001 - Not in POSIX time W009 - schedule_relationship not populated W001 - timestamps not populated W002 - vehicle_id not populated W008 - Header timestamp is older than 65 seconds W004 - vehicle speed is unrealistic Most Frequent Errors and Warnings in GTFS-realtime feeds Number of feeds with error/warning