Impacts of Real-Time Transit Info on Riders
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This research aims to evaluate the positive impacts of deploying OneBusAway, which is a suite of tools that provide real-time bus arrival information through mobile and web applications. OneBusAway was originally developed in Seattle as open source software, and this project conducts a small-scale deployment in Tampa, Florida on the Hillsborough Area Regional Transit (HART) bus system. In the spring of 2013, approximately 250 HART bus riders participated in a pilot program to evaluate the impacts of OneBusAway. Prior to the launch of OneBusAway, these riders completed a “before” web-based survey that included questions about travel behavior, such as frequency of transit travel, waiting times, and transfers, and attitudinal questions pertaining to safety and overall transit service. OneBusAway was then provided to half of the riders (the user group), and it was not given to the other half of riders (the control group). Three months later, both the user and control groups completed an “after” survey to assess their changes in behavior and attitudes due to OneBusAway. We present results from these surveys and accompanying statistical analyses to assess the impacts of this transit traveler information system on bus riders.
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Impacts of Real-Time Transit Info on Riders
- 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
- 8. Mobile Web 8 Smartphone browser Text-only browser
- 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
- Searchable map interface for locating information at the stop level; Supports real-time and static data
- 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)
- Pre wave survey in February 2013; Post-wave survey in May 2013
- Ridership is the key focus of 2 additional studies.