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Policy In Motion: Route360

Policy In Motion: Route360. Bryce Adams, Elizabeth Joseph, Julie Lindsey, Charles E. Maddox, Lauren Waters . 1. Agenda . The Challenge The Solution: Route360 How Does It Work? Will It Work? How Do We Get There? Conclusion Questions and Answers. 2. The Challenge . Citizens

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Policy In Motion: Route360

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  1. Policy In Motion: Route360 Bryce Adams, Elizabeth Joseph, Julie Lindsey, Charles E. Maddox, Lauren Waters 1

  2. Agenda • The Challenge • The Solution: Route360 • How Does It Work? • Will It Work? • How Do We Get There? • Conclusion • Questions and Answers 2

  3. The Challenge Citizens Cannot compare transportation alternatives using a unified platform City Cannot analyze citizens’ transportation preferences and needs 3

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  14. The Challenge Citizens Cannot compare transportation alternatives using a unified platform City Cannot analyze citizens’ transportation preferences and needs 14

  15. The Solution: Route360 Citizens City 15

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  17. How Does Route360 Work? • Pulls information from transportation vendors • Compiles and provides data on: • Trip time • Total cost • Environmental impact • Real-time arrival information • Parking availability • Special event road closures • Collects data on user preferences 17

  18. Research Support 18

  19. The Benefits of Route360 19

  20. How Do We Get There? “Route360: How Austin Gets Around” 20

  21. How Do We Get There? Expenses Revenues Projected Revenue Alternatives Fully funded by the City Public-Private partnerships • Tiered implementation • Phase I: $113,000 • Phase II: $68,000 • Phase III: $58,000 • Projected Expenses • Personnel • App Creation • Marketing 21

  22. How Do We Get There? 22

  23. How Do We Get There? • April 2013: Create City of Austin planning committee. • Summer 2013: Host stakeholder meetings. Open app design competition. • August 2013: Close design competition. Award contract. • January 2014: Begin beta testing. Kick off marketing campaign. • March 2014: Finalize implementation. Rollout app to the entire City of Austin. 23

  24. Conclusion 24

  25. Questions & Answers 25

  26. Works Cited • Dziekan, K. & Kottenhoff, K. (2007). “Dynamic at-stop real-time information displays for public transopt: Effects on customers,” Transportation Research Part A: Policy & Practice, 41(6), p. 489-501. • Ferris, B., Watkins, K., & Borning, K. (2010). “OneBusAway: Results from providing real-time travel information for public transit,” CHI 2010: Bikes & Buses. • Ferris, B. (2011). “OneBusAway: Improving the usability of public transit,” ProQuest Dissertations & Theses. • Watkins, K.E., Ferris, B., Borning, A., Rutherford, G.S., Layton, D. (2011). “Where is my bus? Impact of real-time information on the perceived and actual wait time of transit riders.” Transportation Research Part A: Policy & Practice, 45(8), p. 839-848. • Zhang, F., Shen, Q., & Clifton, K.J. (2008). “Examination of traveler response to real-time information about bus arrivals using panel data,” Transportation Research Record, 2082, p. 107-115. • Tang, L. & Thakuriah, P.V. (2012). “Ridership effect of real-time bus information system: A case study in the City of Chicago,” Transportation Research Part C, 22, p. 146-161. • Budic, I.Z.D. (1994). “Effectiveness of geographic information systems in local planning,” Journal of the American Planning Association, 60(2), p. 244-263. • Johnston, R.A. & de la Barra, T. (2000). “Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems,” Transportation Resarch Part A: Policy & Practice, 34(2), p. 125-136. • Barry, J.J. et. al. (2002). “Origin and estimation in New York City with automated fare system data,” Planning and Administration, 1817, p. 183-187. 26

  27. Proposed Budget 27

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  32. OneBusAway (King Co.) • New interface for existing real-time bus arrival information • Launched summer 2008, steadily increasing use since then • Survey of users (n = 488) recruited through notices • More male & young than general ridership, self-reported • Similar income levels, represents 10% of daily user base • 92% somewhat or much more satisfied with public transit • Cited certainty, ease, and flexibility in comments • Age significantly negatively correlated with satisfaction • 91% reported shorter wait times • 78% said they were more likely to walk to a different route • Statistically significant increase in feelings of safety 32

  33. ShuttleTrac (UMD) • Interface for real-time university shuttle arrival information • Installed summer 2006, implemented spring 2007 • Pre- (n=1679) and Post- (n=1306) launch surveys targeting entire student body • Post survey began only two weeks after launch • Statistically significant improvement in: • Overall satisfaction • Feeling of security at night • Improved perception of on-time performance • No effect on self-reported shuttle trips • Suggests stop location and route changes to increase ridership 33

  34. Bus Tracker (Chicago) • Staggered launches of real-time bus information service • Implemented August 2006 to May 2009 • Longitudinal study over 2002-10, controlling for outside factors • Implementation of Bus Tracker on a route led to: • Statistically significant increase in ridership • An extra 126 rides per day or a ~2% increase • Greater increases in later implementations could signify: • Cumulative effect • More connectivity along later routes 34

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