Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior

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. 3 1. INTRODUCTION This paper describes the development, application, and analysis of a system, in the mobile cloud, named Quantified Traveler (QT). QT is a Computational Travel Feedback System. Travel Feedback is an established programmatic method to change traveler mode choice or trip choice. In a typical travel feedback program, a traveler meets with a counselor who helps her to alternative mode or trip choices that ease loads on the transportation system while satisfying her mobility needs. This research explores whether the successes of travel feedback programs can be replicated without the travel counselor. Our surrogate is a computational system in the mobile cloud. Subjects stream location and movement data into the cloud via personal smartphones. Data Analytics on our server transform the raw data into trip diaries (lists of trips with timing, activity locations, route and mode) and personalized travel footprints, meaning the time, money, calories, and CO2 spent traveling. The end product of the analytics is piped into a set of visualization tools executed on a webpage. The subject uses her browser …

DOI: 10.1080/15472450.2013.856714

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@article{Jariyasunant2015QuantifiedTT, title={Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior}, author={Jerald Jariyasunant and Maya Abou-Zeid and Andre Carrel and Venkatesan N. Ekambaram and David Gaker and Raja Sengupta and Joan L. Walker}, journal={J. Intellig. Transport. Systems}, year={2015}, volume={19}, pages={109-124} }