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Center for Urban Transportation Research | University of South Florida
OneBusAway Multi-region
Rapidly Expanding Mobile
Transit Apps to New Cities
Sean J. Barbeau, Ph.D.
2
Background
• Real-time transit information has many benefits
– Shorter perceived wait time [1]
– Shorter actual wait time[1]
– Lowers learning curve for new riders [2]
– Increased ridership (maybe?) [3]
– Increased feeling of safety (e.g., at night) [5][6]
• Riders prefer accessing real-time transit info via
mobile apps[1]
[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. 1807-181
[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.
Tony Kurdzuk/The Star-Ledger
3
Challenge
• Custom mobile apps are expensive
– Some estimates > $150,000k for a single platform [7]
– Doesn’t include maintenance cost
• Implementing and maintaining custom apps on all
popular smartphone platforms is cost-prohibitive
• Open data is good, but doesn’t always result in
apps by 3rd party developers
• How can we cost-effectively launch mobile transit
apps in new cities?
[7] Larry Lauvray "iPad App Development Cost - A Breakdown." Propelics Blog, Vol. Accessed at: http://www.propelics.com/ipad-app-development-cost-a-breakdown/
4
OneBusAway
• Open-source real-time transit information
system
• Originally developed at University of
Washington
– Ph.D. work of Brian Ferris and Kari Watkins
– Used in multiple research studies to
understand how real-time info affects
transit riders
• Includes server-side software
– Process bulk real-time transit info
– Provides Application Programming Interface
(API) for apps
• Includes mobile apps for:
– iPhone
– Android
– Windows Phone
– Windows 8
http://onebusaway.org
5
OneBusAway – Mobile Apps
Android Windows Phone &
Windows 8
iPhone
Support user location, route, stop contextual/personalized information
All OPEN-SOURCE!
6
OneBusAway
• 2012 – Mobile apps
only available in
Puget Sound
• How do we expand
them to new cities?
http://onebusaway.org
7
Original OneBusAway mobile app
design
8
Why don’t we duplicate the mobile
apps for each city?
• Creates app
maintenance
work for each
city, per platform
• Clutters app
stores
• Fragments
source code
9
OneBusAway “multi-region” design
• Each region maintains its own OneBusAway
server software, but uses the same mobile
apps
– Reduces burden on regions to maintain apps
– Eliminates burden on a centralized entity to
maintain data quality control, servers, and
customer support for each new region
– Doesn’t clutter app stores – all users download
the same “OneBusAway” app for all regions
• “You bring the server, we bring the apps”
10
Multi-region architecture
• Region
information is
stored in
centralized server
directory (i.e.,
Regions API)
• Apps now find
nearby regions
using Regions API
11
OneBusAway Server Directory
12
OBA – Android app
13
New OneBusAway Region Checklist
 Transit Data in GTFS format
 AVL system that provides arrival estimates
 Implement a GTFS-realtime (or SIRI) feed
 Set up a OneBusAway Server
 Do some quality-control testing
 Launch OneBusAway apps in new city!
• Via request to onebusway-developers group!
14
Adding OneBusAway regions to apps
• Following the request to the onebusaway_developer
group, the new region can be added
• Two stages for a new region:
1. Experimental:
• Regions in development
• Users can enable in iPhone and Android apps via “Settings->Enable
Experimental Regions”
2. Production:
• Meets a certain standard in terms of quality and quantity of real-
time data
• Region is available in all apps by default
• See http://goo.gl/ydbc0c for details
15
ONEBUSAWAY TAMPA
Setting up a new OneBusAway region – a case study
16
New OneBusAway Region Checklist
 Transit Data in GTFS format
 AVL system that provides arrival estimates
 Implement a GTFS-realtime (or SIRI) feed
 Set up a OneBusAway Server
 Do some quality-control testing
 Launch OneBusAway apps in new city!
- Here’s where we started in Tampa…
17
HART AVL
OrbCAD
SQL Server
HART
USF
OneBusAway
HART
Buses
HART
Comm.
Tower
Trip/
Vehicle
Updates
USF
OneBusAway
server
USF
GTFS-realtime
USF
GTFS-realtime
server
Real-time
info
request
Real-time
info
response
Real-time
info
request
Real-time
info
response
Creating a new region - Tampa
1. Establish a GTFS-realtime feed
GTFS-realtime software is open-source :
https://github.com/CUTR-at-USF/HART-GTFS-realtimeGenerator/wiki
18
HART AVL
OrbCAD
SQL Server
HART
USF
OneBusAway
HART
Buses
HART
Comm.
Tower
Trip/
Vehicle
Updates
USF
OneBusAway
server
USF
GTFS-realtime
USF
GTFS-realtime
server
Real-time
info
request
Real-time
info
response
Real-time
info
request
Real-time
info
response
Creating a new region - Tampa
2. Configure OneBusAway software
GTFS-realtime software is open-source :
https://github.com/CUTR-at-USF/HART-GTFS-realtimeGenerator/wiki
19
GTFS-realtime format (in plain text)
trip_update {
trip {
trip_id: "974372"
}
stop_time_update {
stop_sequence: 17
arrival {
delay: -180
uncertainty: 30
}
stop_id: "571"
}
vehicle {
id: "1301"
}
}
Estimated Arrival Times (TripUpdate)
Data displayed in
mobile apps
20
GTFS-realtime format (in plain text)
trip_update {
trip {
trip_id: "974372"
}
stop_time_update {
stop_sequence: 17
arrival {
delay: -180
uncertainty: 30
}
stop_id: "571"
}
vehicle {
id: "1301"
}
}
vehicle {
trip {
trip_id: "974372"
}
position {
latitude: 28.02931
longitude: -82.456566
bearing: 360.0
speed: 0.0
}
vehicle {
id: "1301"
}
}
Estimated Arrival Times (TripUpdate) Vehicle Locations (VehiclePositions)
Data displayed in
mobile apps
Not currently used by
mobile apps
21
OBA – Android app
Delay value
Arrival
estimate,
based on
real-time
delay
22
Challenges – Technology / Process
Challenge Solution / Lesson Learned
Old documentation for OneBusAway at the
start of the project
Create new documentation!
Painful at first, but helps others
Unknown accuracy of arrival times from
vendor AVL
On-the-ground testing and validation
necessary
After several iterations, got good results!
Communication with various parties
• Agency ITS staff
• Agency IT staff
• Agency Marketing staff
• Vendor
Get upper-management buy-in for Agency,
have in-person meetings. Identify
champion within agency.
Takes time, but reduces overall turnaround time for requests
OneBusAway Tampa
23
Challenge Solution / Lesson Learned
GTFS - arrival time for Stop A is after arrival
time for Stop B during trip
Work with agency to resolve problem
Show the agency error in software, create documentation to
explain the current data issues with examples
GTFS - Seconds resolution (“HH:MM:SS” )
for time not included
”
GTFS - Incorrect route URLs prevented app
users from seeing schedules ”
AVL - tripIDs not matching GTFS tripIDs Examine data dictionary for AVL system,
talk directly to vendor
Conference call helped resolve issue
AVL - Flipped +/- for delay value Extensive troubleshooting and isolation of
issue, talk directly to vendor
Finally resulted in on-site meeting, where we resolved the
problem
AVL – Agency database replication issues
”
AVL - Use “deviation” or
“predicted_deviation” value?
On-the-ground testing and validation
necessary
After several iterations, got good results!
Challenges – Data
OneBusAway Tampa
24
Tampa - From pilot to production
• USF launched a pilot of OneBusAway in Tampa
with approximately 200 users in February 2013.
– Partnered with Georgia Tech to do controlled study of
impact of real-time info on riders
– USF maintained OneBusAway for the pilot
• Public launch – August 2013
– HART adopted OneBusAway Tampa, now runs on their
servers (tampa.onebusaway.org)
– USF assisted HART in preparing RFP for long-term
vendor support (began February 2014)
25
LESSONS LEARNED &
CONCLUSIONS
The “take-away”
26
Lessons Learned
• Open-source software enabled this project – many
contributors
– Git and Github are huge enablers
• Volunteer developers are great for general
advancement of the project, but for time-sensitive, or
specific, tasks paid developers may be required
• Identifying an on-going funding source is important for
limited centralized operations (e.g., review and
merging of software contributions from community)
• Pattern of “tech demo -> production” region
deployments seems to be emerging
27
Conclusions
• OneBusAway mobile apps in new cities:
– Tampa (tampa.onebusaway.org – Hillsborough Area Regional Transit)
– Atlanta (atlanta.onebusaway.org – Georgia Tech, w/ data from MARTA)
– Washington, D.C. (tech demo - http://oba.mobilitylab.org/ - Mobility Lab)
– York Region, Canada (tech demo – York Region Transit)
– (More soon)!
• OneBusAway multi-region -> easy to add new
cities in the future
– Sustainable, scalable, low-cost, and low-maintenance
model
28www.onebusaway.org
29
Future work
• Ongoing research to understand impact of real-
time info on riders
– Helps us understand what users want, how to
encourage use of non-single occupancy vehicle modes
– Justifies investments in the technology
• New features
– Improved issue reporting
– Contributions from deployments
– OneBusAway for Google Glass
– Others…
30
Acknowledgements
• Full acknowledgements for OneBusAway Multi-
region Initiative are at:
– http://bit.ly/OBA_multiregion_blog
• Funding for USF’s work provided by the National
Center for Transit Research
• Hillsborough Area Regional Transit, for data and
support of the OneBusAway Tampa public
deployment
• University of Washington and Georgia Tech, for
continued involvement in the project
• All OneBusAway community members
31
Thanks!
Sean J. Barbeau, Ph.D.
barbeau@cutr.usf.edu
813.974.7208

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2014 CUTR Webinar - OneBusAway Multi-region – Rapidly expanding mobile transit apps to new cities

  • 1. Center for Urban Transportation Research | University of South Florida OneBusAway Multi-region Rapidly Expanding Mobile Transit Apps to New Cities Sean J. Barbeau, Ph.D.
  • 2. 2 Background • Real-time transit information has many benefits – Shorter perceived wait time [1] – Shorter actual wait time[1] – Lowers learning curve for new riders [2] – Increased ridership (maybe?) [3] – Increased feeling of safety (e.g., at night) [5][6] • Riders prefer accessing real-time transit info via mobile apps[1] [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. 1807-181 [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. Tony Kurdzuk/The Star-Ledger
  • 3. 3 Challenge • Custom mobile apps are expensive – Some estimates > $150,000k for a single platform [7] – Doesn’t include maintenance cost • Implementing and maintaining custom apps on all popular smartphone platforms is cost-prohibitive • Open data is good, but doesn’t always result in apps by 3rd party developers • How can we cost-effectively launch mobile transit apps in new cities? [7] Larry Lauvray "iPad App Development Cost - A Breakdown." Propelics Blog, Vol. Accessed at: http://www.propelics.com/ipad-app-development-cost-a-breakdown/
  • 4. 4 OneBusAway • Open-source real-time transit information system • Originally developed at University of Washington – Ph.D. work of Brian Ferris and Kari Watkins – Used in multiple research studies to understand how real-time info affects transit riders • Includes server-side software – Process bulk real-time transit info – Provides Application Programming Interface (API) for apps • Includes mobile apps for: – iPhone – Android – Windows Phone – Windows 8 http://onebusaway.org
  • 5. 5 OneBusAway – Mobile Apps Android Windows Phone & Windows 8 iPhone Support user location, route, stop contextual/personalized information All OPEN-SOURCE!
  • 6. 6 OneBusAway • 2012 – Mobile apps only available in Puget Sound • How do we expand them to new cities? http://onebusaway.org
  • 8. 8 Why don’t we duplicate the mobile apps for each city? • Creates app maintenance work for each city, per platform • Clutters app stores • Fragments source code
  • 9. 9 OneBusAway “multi-region” design • Each region maintains its own OneBusAway server software, but uses the same mobile apps – Reduces burden on regions to maintain apps – Eliminates burden on a centralized entity to maintain data quality control, servers, and customer support for each new region – Doesn’t clutter app stores – all users download the same “OneBusAway” app for all regions • “You bring the server, we bring the apps”
  • 10. 10 Multi-region architecture • Region information is stored in centralized server directory (i.e., Regions API) • Apps now find nearby regions using Regions API
  • 13. 13 New OneBusAway Region Checklist  Transit Data in GTFS format  AVL system that provides arrival estimates  Implement a GTFS-realtime (or SIRI) feed  Set up a OneBusAway Server  Do some quality-control testing  Launch OneBusAway apps in new city! • Via request to onebusway-developers group!
  • 14. 14 Adding OneBusAway regions to apps • Following the request to the onebusaway_developer group, the new region can be added • Two stages for a new region: 1. Experimental: • Regions in development • Users can enable in iPhone and Android apps via “Settings->Enable Experimental Regions” 2. Production: • Meets a certain standard in terms of quality and quantity of real- time data • Region is available in all apps by default • See http://goo.gl/ydbc0c for details
  • 15. 15 ONEBUSAWAY TAMPA Setting up a new OneBusAway region – a case study
  • 16. 16 New OneBusAway Region Checklist  Transit Data in GTFS format  AVL system that provides arrival estimates  Implement a GTFS-realtime (or SIRI) feed  Set up a OneBusAway Server  Do some quality-control testing  Launch OneBusAway apps in new city! - Here’s where we started in Tampa…
  • 19. 19 GTFS-realtime format (in plain text) trip_update { trip { trip_id: "974372" } stop_time_update { stop_sequence: 17 arrival { delay: -180 uncertainty: 30 } stop_id: "571" } vehicle { id: "1301" } } Estimated Arrival Times (TripUpdate) Data displayed in mobile apps
  • 20. 20 GTFS-realtime format (in plain text) trip_update { trip { trip_id: "974372" } stop_time_update { stop_sequence: 17 arrival { delay: -180 uncertainty: 30 } stop_id: "571" } vehicle { id: "1301" } } vehicle { trip { trip_id: "974372" } position { latitude: 28.02931 longitude: -82.456566 bearing: 360.0 speed: 0.0 } vehicle { id: "1301" } } Estimated Arrival Times (TripUpdate) Vehicle Locations (VehiclePositions) Data displayed in mobile apps Not currently used by mobile apps
  • 21. 21 OBA – Android app Delay value Arrival estimate, based on real-time delay
  • 22. 22 Challenges – Technology / Process Challenge Solution / Lesson Learned Old documentation for OneBusAway at the start of the project Create new documentation! Painful at first, but helps others Unknown accuracy of arrival times from vendor AVL On-the-ground testing and validation necessary After several iterations, got good results! Communication with various parties • Agency ITS staff • Agency IT staff • Agency Marketing staff • Vendor Get upper-management buy-in for Agency, have in-person meetings. Identify champion within agency. Takes time, but reduces overall turnaround time for requests OneBusAway Tampa
  • 23. 23 Challenge Solution / Lesson Learned GTFS - arrival time for Stop A is after arrival time for Stop B during trip Work with agency to resolve problem Show the agency error in software, create documentation to explain the current data issues with examples GTFS - Seconds resolution (“HH:MM:SS” ) for time not included ” GTFS - Incorrect route URLs prevented app users from seeing schedules ” AVL - tripIDs not matching GTFS tripIDs Examine data dictionary for AVL system, talk directly to vendor Conference call helped resolve issue AVL - Flipped +/- for delay value Extensive troubleshooting and isolation of issue, talk directly to vendor Finally resulted in on-site meeting, where we resolved the problem AVL – Agency database replication issues ” AVL - Use “deviation” or “predicted_deviation” value? On-the-ground testing and validation necessary After several iterations, got good results! Challenges – Data OneBusAway Tampa
  • 24. 24 Tampa - From pilot to production • USF launched a pilot of OneBusAway in Tampa with approximately 200 users in February 2013. – Partnered with Georgia Tech to do controlled study of impact of real-time info on riders – USF maintained OneBusAway for the pilot • Public launch – August 2013 – HART adopted OneBusAway Tampa, now runs on their servers (tampa.onebusaway.org) – USF assisted HART in preparing RFP for long-term vendor support (began February 2014)
  • 26. 26 Lessons Learned • Open-source software enabled this project – many contributors – Git and Github are huge enablers • Volunteer developers are great for general advancement of the project, but for time-sensitive, or specific, tasks paid developers may be required • Identifying an on-going funding source is important for limited centralized operations (e.g., review and merging of software contributions from community) • Pattern of “tech demo -> production” region deployments seems to be emerging
  • 27. 27 Conclusions • OneBusAway mobile apps in new cities: – Tampa (tampa.onebusaway.org – Hillsborough Area Regional Transit) – Atlanta (atlanta.onebusaway.org – Georgia Tech, w/ data from MARTA) – Washington, D.C. (tech demo - http://oba.mobilitylab.org/ - Mobility Lab) – York Region, Canada (tech demo – York Region Transit) – (More soon)! • OneBusAway multi-region -> easy to add new cities in the future – Sustainable, scalable, low-cost, and low-maintenance model
  • 29. 29 Future work • Ongoing research to understand impact of real- time info on riders – Helps us understand what users want, how to encourage use of non-single occupancy vehicle modes – Justifies investments in the technology • New features – Improved issue reporting – Contributions from deployments – OneBusAway for Google Glass – Others…
  • 30. 30 Acknowledgements • Full acknowledgements for OneBusAway Multi- region Initiative are at: – http://bit.ly/OBA_multiregion_blog • Funding for USF’s work provided by the National Center for Transit Research • Hillsborough Area Regional Transit, for data and support of the OneBusAway Tampa public deployment • University of Washington and Georgia Tech, for continued involvement in the project • All OneBusAway community members
  • 31. 31 Thanks! Sean J. Barbeau, Ph.D. barbeau@cutr.usf.edu 813.974.7208