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Evaluating the Impacts of Real-Time Transit
Information on Bus Riders in Tampa, Florida
Candace Brakewood, PhD Candidate in Civil & Environmental Engineering, Georgia Tech
Dr. Kari Watkins, Assistant Professor of Civil & Environmental Engineering, Georgia Tech
Dr. Sean Barbeau, Principal Mobile Software Architect for R&D, University of South Florida
APTA Bus, Kansas City, MO
May 5, 2014
Overview
• Background on OneBusAway
• OneBusAway Interfaces
• Research in Tampa
2
What is OneBusAway?
• What? Suite of tools that
provides real-time bus/train
tracking information
– Open source software
– Free to riders
• Why? Make riding public transit
easier by providing good
information in usable formats
– Research to evaluate the impacts
3
iPhone App
Where is OneBusAway?
4
Seattle WA:
Original deployment
New York, NY:
Adapted for the MTA
(Bus Time)
Washington, DC: Beta
Atlanta, GA:
Launched in
early fall 2013
Tampa, FL:
Launched in late
summer 2013
York, CA:
Beta
How do you use OneBusAway?
5
ONEBUSAWAY INTERFACES
6
Website
onebusaway.org 7
Mobile Web
8
Smartphone browser Text-only browser
Mobile Apps
Android
Windows Phone &
Windows 8
iPhone
9
Mobile App Features
• Location-aware
• Bookmarking
• Service alerts
• Problem
reporting
10
Android App
Sign Mode
• Web interface optimized for monitor display
• Multiple route and stop selection capabilities
– E.g., showing a cluster of stops outside a coffee shop
• Set-up with Monitor & Google Chromecast
11
Image source: www.google.com/chromecast
TAMPA RESEARCH PROJECT
How does real time information change user
perceptions and behavior?
12
Key Prior Studies
Decreased
Wait Times
•Watkins et al.
(2011)
•Location:
Seattle, King
County Metro
•Conclusion:
Both actual wait
times and
perceived wait
times of real-
time bus
information
users were less
than non-users
could
lead to
Increased
Satisfaction
•Zhang, Shen &
Clifton (2008)
•Location:
University of
Maryland
•Conclusion:
Overall
satisfaction with
transit service
increased due to
real-time shuttle
bus information
could
lead to
Increased
Ridership
•Tang &
Thakuriah
(2012)
•Location:
CTA, Chicago
•Conclusion:
Modest increase
in ridership (126
rides/route on
average
weekday)
attributable to
real-time bus
information
1. Watkins, K. E., Ferris, B., Borning, A., Rutherford, G. S., & Layton, D. (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, 45(8), 839–848.
2. Zhang, F., Shen, Q., & Clifton, K. J. (2008). Examination of Traveler Responses to Real-Time Information About Bus Arrivals Using
Panel Data. Transportation Research Record: Journal of the Transportation Research Board, 2082, 107–115.
3. Tang, L., & Thakuriah, P. (Vonu). (2012). Ridership effects of real-time bus information system: A case study in the City of Chicago.
Transportation Research Part C: Emerging Technologies, 22, 146–161.
13
Methodology:
Before-After Control Group
• Motivation: HART provided USF & Georgia Tech
special access to real-time data
• Recruitment: HART website/email list
(Incentive of 1 day bus pass)
• Measurement: Web-based surveys
• Group Assignment: Random number generator
• User Group: 5 interfaces of OneBusAway
(3 websites & 2 smartphone apps)
• Study Period: 3 months
Android App
14
Analysis of Usual Wait Times
3%3% 31% 38% 26%
0% 50% 100%
I spend much more time waiting
I spend somewhat more time waiting
I spend about the same time waiting
I spend somewhat less time waiting
I spend much less time waiting
• Identical questions about usual wait time on regular route on the before and after surveys
Usual Wait Time
(minutes)
Sample Size Before After Difference
n Mean (SD) Mean (SD) Mean
Control Group 102
10.71 10.50
-0.21
(3.88) (4.25)
OneBusAway Group 107
11.36 9.56
-1.79
(4.06) (4.68)
Comparison Difference of Means: t=2.65, two-tailed p=0.009 < 0.01
• Experimental group post-wave survey only: Has using OneBusAway changed the amount of
time you wait at the bus stop?
Bottom graphic: n=109. Figures rounded to the nearest whole percent.
15
Analysis of Feelings
While Waiting for the Bus
• Experimental group post-wave survey only asked: Since you began using OneBusAway, do
you feel more relaxed when waiting for the bus?
• Identical questions about feelings while waiting asked on the before and after surveys
28% 40% 27% 4%
0% 50% 100%
Agree strongly
Agree somewhat
Neutral
Disagree somewhat
Disagree strongly
Bottom graphic: n=108; Figures rounded to the nearest whole percent.
Control Group OneBusAway User Group Diff. in Gain Scores
% Frequently + Always % Frequently + Always Wilcoxon Test
Feelings Before After Before After W p-value
Productive 11% 10% 10% 17% 6201 0.051 *
Anxious 18% 19% 26% 25% 4548 0.082 *
Relaxed 34% 34% 27% 25% 5518 0.592
Frustrated 24% 26% 25% 18% 4241 0.006 ***
Significance: * p<0.10; ** p<0.05; *** p<0.01
16
Analysis of Satisfaction
• Experimental group post-wave survey only asked: Since you began using OneBusAway, do you
feel more satisfied riding HART buses?
• Identical questions about satisfaction asked on the before and after surveys
32% 38% 26% 3%
0% 50% 100%
Agree strongly
Agree somewhat
Neutral
Disagree somewhat
Disagree strongly
Bottom graphic: n=107
Figures rounded to the nearest whole percent.
Control Group OneBusAway Group Diff. in Gain Scores
% Satisfied % Satisfied Wilcoxon Test
Before After Before After W p-value
How frequently the bus comes 37% 41% 40% 44% 5812 0.459
How long you have to wait for the bus 39% 34% 36% 46% 6425 0.020 **
How often the bus arrives at the stop on time 54% 45% 45% 59% 7094 0.0001 ***
How often you arrive at your destination on time 57% 53% 55% 63% 5835 0.236
How often you have to transfer buses to get to your destination 44% 42% 38% 36% 4916 0.342
Overall HART bus service 63% 59% 57% 58% 5717 0.410
Significance: * p<0.10; ** p<0.05; *** p<0.01
17
Analysis of Bus Trips/Week
• Identical questions about the number of HART bus trips/week on the before and after surveys
Bottom graphic: n=108. 0% selected “I ride somewhat less.” Figures rounded to the nearest whole percent.
Trips/Week
Sample Size Before After Difference
n Mean (SD) Mean (SD) Mean
Control Group 107
7.03 6.63
-0.40
(3.79) (4.09)
Experimental Group 110
7.09 6.40
-0.69
(3.94) (3.71)
Comparison Difference of Means: t=0.66, two-tailed p=0.512
• Experimental group post-wave survey only: Has using OneBusAway changed the number of
HART bus trips that you take?
20% 19% 60% 1%
0% 50% 100%
I ride much more often
I ride somewhat more
I ride about the same
I ride much less
18
Conclusions
• Significant improvements in the waiting experience
– Decreases in self-reported usual wait times
– Decreases in negative feelings, particularly frustration
– Increases in satisfaction with wait times
• Little evidence supporting a change in transit trips
– Approx. 1/3 of RTI users stated they ride the bus more frequently,
perhaps because of:
• Affirmation bias of respondents
• Scale of measurement (trips per week)
– Only riders within sphere of transit agency
• Check out OneBusAway at onebusaway.org
– Especially if you want to launch OneBusAway in your region!
19
20
QUESTIONS?
Contact Information
Candace Brakewood: candace.brakewood@gatech.edu
Sean Barbeau: barbeau@cutr.usf.edu
Kari Watkins: kari.watkins@ce.gatech.edu
Acknowledgements: This work was funded by a US DOT Eisenhower Graduate
Fellowship, the National Center for Transit Research (NCTR), and the National
Center for Transportation Systems Productivity and Management (NCTSPM). I am
also very grateful to the Hillsborough Area Regional Transit Authority (HART) for
their support, particularly Shannon Haney.
Appendix: New 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!
21
Appendix: Limitations
• Length of Study
– June 2013 BRT opening in Tampa
• Representativeness of sample to all
HART riders
– More Caucasian respondents
– Higher household income levels
– Higher levels of car ownership (but
fewer licenses)
• Applicability beyond Tampa
– Limited to transit-dependent
populations BRT Stop
22

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APTA 2014 - Evaluating the Impacts of Real-Time Transit Information on Bus Riders in Tampa, Florida

  • 1. Evaluating the Impacts of Real-Time Transit Information on Bus Riders in Tampa, Florida Candace Brakewood, PhD Candidate in Civil & Environmental Engineering, Georgia Tech Dr. Kari Watkins, Assistant Professor of Civil & Environmental Engineering, Georgia Tech Dr. Sean Barbeau, Principal Mobile Software Architect for R&D, University of South Florida APTA Bus, Kansas City, MO May 5, 2014
  • 2. Overview • Background on OneBusAway • OneBusAway Interfaces • Research in Tampa 2
  • 3. What is OneBusAway? • What? Suite of tools that provides real-time bus/train tracking information – Open source software – Free to riders • Why? Make riding public transit easier by providing good information in usable formats – Research to evaluate the impacts 3 iPhone App
  • 4. Where is OneBusAway? 4 Seattle WA: Original deployment New York, NY: Adapted for the MTA (Bus Time) Washington, DC: Beta Atlanta, GA: Launched in early fall 2013 Tampa, FL: Launched in late summer 2013 York, CA: Beta
  • 5. How do you use OneBusAway? 5
  • 9. Mobile Apps Android Windows Phone & Windows 8 iPhone 9
  • 10. Mobile App Features • Location-aware • Bookmarking • Service alerts • Problem reporting 10 Android App
  • 11. Sign Mode • Web interface optimized for monitor display • Multiple route and stop selection capabilities – E.g., showing a cluster of stops outside a coffee shop • Set-up with Monitor & Google Chromecast 11 Image source: www.google.com/chromecast
  • 12. TAMPA RESEARCH PROJECT How does real time information change user perceptions and behavior? 12
  • 13. Key Prior Studies Decreased Wait Times •Watkins et al. (2011) •Location: Seattle, King County Metro •Conclusion: Both actual wait times and perceived wait times of real- time bus information users were less than non-users could lead to Increased Satisfaction •Zhang, Shen & Clifton (2008) •Location: University of Maryland •Conclusion: Overall satisfaction with transit service increased due to real-time shuttle bus information could lead to Increased Ridership •Tang & Thakuriah (2012) •Location: CTA, Chicago •Conclusion: Modest increase in ridership (126 rides/route on average weekday) attributable to real-time bus information 1. Watkins, K. E., Ferris, B., Borning, A., Rutherford, G. S., & Layton, D. (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, 45(8), 839–848. 2. Zhang, F., Shen, Q., & Clifton, K. J. (2008). Examination of Traveler Responses to Real-Time Information About Bus Arrivals Using Panel Data. Transportation Research Record: Journal of the Transportation Research Board, 2082, 107–115. 3. Tang, L., & Thakuriah, P. (Vonu). (2012). Ridership effects of real-time bus information system: A case study in the City of Chicago. Transportation Research Part C: Emerging Technologies, 22, 146–161. 13
  • 14. Methodology: Before-After Control Group • Motivation: HART provided USF & Georgia Tech special access to real-time data • Recruitment: HART website/email list (Incentive of 1 day bus pass) • Measurement: Web-based surveys • Group Assignment: Random number generator • User Group: 5 interfaces of OneBusAway (3 websites & 2 smartphone apps) • Study Period: 3 months Android App 14
  • 15. Analysis of Usual Wait Times 3%3% 31% 38% 26% 0% 50% 100% I spend much more time waiting I spend somewhat more time waiting I spend about the same time waiting I spend somewhat less time waiting I spend much less time waiting • Identical questions about usual wait time on regular route on the before and after surveys Usual Wait Time (minutes) Sample Size Before After Difference n Mean (SD) Mean (SD) Mean Control Group 102 10.71 10.50 -0.21 (3.88) (4.25) OneBusAway Group 107 11.36 9.56 -1.79 (4.06) (4.68) Comparison Difference of Means: t=2.65, two-tailed p=0.009 < 0.01 • Experimental group post-wave survey only: Has using OneBusAway changed the amount of time you wait at the bus stop? Bottom graphic: n=109. Figures rounded to the nearest whole percent. 15
  • 16. Analysis of Feelings While Waiting for the Bus • Experimental group post-wave survey only asked: Since you began using OneBusAway, do you feel more relaxed when waiting for the bus? • Identical questions about feelings while waiting asked on the before and after surveys 28% 40% 27% 4% 0% 50% 100% Agree strongly Agree somewhat Neutral Disagree somewhat Disagree strongly Bottom graphic: n=108; Figures rounded to the nearest whole percent. Control Group OneBusAway User Group Diff. in Gain Scores % Frequently + Always % Frequently + Always Wilcoxon Test Feelings Before After Before After W p-value Productive 11% 10% 10% 17% 6201 0.051 * Anxious 18% 19% 26% 25% 4548 0.082 * Relaxed 34% 34% 27% 25% 5518 0.592 Frustrated 24% 26% 25% 18% 4241 0.006 *** Significance: * p<0.10; ** p<0.05; *** p<0.01 16
  • 17. Analysis of Satisfaction • Experimental group post-wave survey only asked: Since you began using OneBusAway, do you feel more satisfied riding HART buses? • Identical questions about satisfaction asked on the before and after surveys 32% 38% 26% 3% 0% 50% 100% Agree strongly Agree somewhat Neutral Disagree somewhat Disagree strongly Bottom graphic: n=107 Figures rounded to the nearest whole percent. Control Group OneBusAway Group Diff. in Gain Scores % Satisfied % Satisfied Wilcoxon Test Before After Before After W p-value How frequently the bus comes 37% 41% 40% 44% 5812 0.459 How long you have to wait for the bus 39% 34% 36% 46% 6425 0.020 ** How often the bus arrives at the stop on time 54% 45% 45% 59% 7094 0.0001 *** How often you arrive at your destination on time 57% 53% 55% 63% 5835 0.236 How often you have to transfer buses to get to your destination 44% 42% 38% 36% 4916 0.342 Overall HART bus service 63% 59% 57% 58% 5717 0.410 Significance: * p<0.10; ** p<0.05; *** p<0.01 17
  • 18. Analysis of Bus Trips/Week • Identical questions about the number of HART bus trips/week on the before and after surveys Bottom graphic: n=108. 0% selected “I ride somewhat less.” Figures rounded to the nearest whole percent. Trips/Week Sample Size Before After Difference n Mean (SD) Mean (SD) Mean Control Group 107 7.03 6.63 -0.40 (3.79) (4.09) Experimental Group 110 7.09 6.40 -0.69 (3.94) (3.71) Comparison Difference of Means: t=0.66, two-tailed p=0.512 • Experimental group post-wave survey only: Has using OneBusAway changed the number of HART bus trips that you take? 20% 19% 60% 1% 0% 50% 100% I ride much more often I ride somewhat more I ride about the same I ride much less 18
  • 19. Conclusions • Significant improvements in the waiting experience – Decreases in self-reported usual wait times – Decreases in negative feelings, particularly frustration – Increases in satisfaction with wait times • Little evidence supporting a change in transit trips – Approx. 1/3 of RTI users stated they ride the bus more frequently, perhaps because of: • Affirmation bias of respondents • Scale of measurement (trips per week) – Only riders within sphere of transit agency • Check out OneBusAway at onebusaway.org – Especially if you want to launch OneBusAway in your region! 19
  • 20. 20 QUESTIONS? Contact Information Candace Brakewood: candace.brakewood@gatech.edu Sean Barbeau: barbeau@cutr.usf.edu Kari Watkins: kari.watkins@ce.gatech.edu Acknowledgements: This work was funded by a US DOT Eisenhower Graduate Fellowship, the National Center for Transit Research (NCTR), and the National Center for Transportation Systems Productivity and Management (NCTSPM). I am also very grateful to the Hillsborough Area Regional Transit Authority (HART) for their support, particularly Shannon Haney.
  • 21. Appendix: New 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! 21
  • 22. Appendix: Limitations • Length of Study – June 2013 BRT opening in Tampa • Representativeness of sample to all HART riders – More Caucasian respondents – Higher household income levels – Higher levels of car ownership (but fewer licenses) • Applicability beyond Tampa – Limited to transit-dependent populations BRT Stop 22

Editor's Notes

  1. Searchable map interface for locating information at the stop level; Supports real-time and static data
  2. Seattle: Actual wait times of real-time users were almost 2 minutes less than non-users. Perceived wait times of riders with real-time information 31% less Chicago: A panel regression model from 2002-2010 showed real-time information caused a “modest” increase in ridership (126 rides per route on an average weekday)
  3. Pre wave survey in February 2013; Post-wave survey in May 2013
  4. Ridership is the key focus of 2 additional studies.