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Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior

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  • Jariyasunant, Jerald
  • Abou-Zeid, Maya
  • Carrel, Andre
  • Ekambaram, Venkatesan
  • Gaker, David
  • Sengupta, Raja
  • Walker, Joan L.

Abstract

We describe the design and evaluation of a system named Quantified Traveler (QT). QT is a Computational Travel Feedback System. Travel Feedback is an established programmatic method whereby travelers record travel in diaries, and meet with a counselor who guides her to alternate mode or trip decisions that are more sustainable or otherwise beneficial to society, while still meeting the subject’s mobility needs. QT is a computation surrogate for the counselor. Since counselor costs can limit the size of travel feedback programs, a system such as QT at the low costs of cloud computing, could dramatically increase scale, and thereby sustainable travel. QT uses an app on the phone to collect travel data, a server in the cloud to process it into travel diaries and then a personalized carbon, exercise, time, and cost footprint. The subject is able to see all of this information on the web. We evaluate with 135 subjects to learn if subjects let us use their personal phones and data-plans to build travel diaries, whether they actually use the website to look at their travel information, whether the design creates pro-environmental shifts in psychological variables measured by entry and exit surveys, and finally whether the revealed travel behavior records reduced driving. Before and after statistical analysis and the results from a structural equation model suggest that the results are a qualified success.

Suggested Citation

  • Jariyasunant, Jerald & Abou-Zeid, Maya & Carrel, Andre & Ekambaram, Venkatesan & Gaker, David & Sengupta, Raja & Walker, Joan L., 2013. "Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior," University of California Transportation Center, Working Papers qt2dh952gj, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt2dh952gj
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    1. Chester, Mikhail V, 2008. "Life-cycle Environmental Inventory of Passenger Transportation in the United States," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7n29n303, Institute of Transportation Studies, UC Berkeley.
    2. Chen, Ching-Fu & Lai, Wen-Tai, 2011. "The effects of rational and habitual factors on mode choice behaviors in a motorcycle-dependent region: Evidence from Taiwan," Transport Policy, Elsevier, vol. 18(5), pages 711-718, September.
    3. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    4. Choo, Sangho & Mokhtarian, Patricia L., 2004. "What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(3), pages 201-222, March.
    5. Tim Schwanen & Patricia L. Mokhtarian, 2007. "Attitudes toward travel and land use and choice of residential neighborhood type: Evidence from the San Francisco bay area," Housing Policy Debate, Taylor & Francis Journals, vol. 18(1), pages 171-207, January.
    6. Vij, Akshay & Carrel, André & Walker, Joan L., 2013. "Incorporating the influence of latent modal preferences on travel mode choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 164-178.
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    Keywords

    Engineering; sustainable transportation; computational travel feedback;
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