UC Berkeley

The recent growth of smartphones along with cheap, scalable cloud computing infrastructure has allowed for a plethora of new applications to be built. In transportation, two main efforts have been greatly impacted by this, delivering better traveler information to users, and collecting travel behavior information for researchers. This thesis describes 4 major efforts along these two themes; the development of a real-time transit trip planner, the evaluation of the value of real- time data, the development of a smartphone based automated travel diary system, and the design and evaluation of a behavior change experiment using the travel diary system. The first half of the thesis describes the technical development of the real-time transit trip planner along with experiments showing the positive impacts to travelers. Prior to this work, transit trip planners primarily used schedule data to route people through a transit network. This work is the first solution to the K- shortest paths problem to use real-time transit arrival data retrieved from a third party API. The algorithm then was implemented in an application called BayTripper, which serves over 1,000 users in the San Francisco Bay Area. The second half of the thesis describes the technical development of the automated travel diary system, which consists of battery efficient smartphone applications, server infrastructure to process data with trip determination algorithms, and web tools used to evaluate the accuracy of the system. The contribution to the literature is a catalogue of problems and related algorithmic solutions to building an end-to-end, battery efficient, automated travel diary. A behavior change experiment was designed and run using the automated travel diary system, which showed the potential for

 changes

 in

 users' awareness of their travel behavior, intentions to change, and short-term behavior change. This experiment represents a large scale test of the automated travel diary system, as well as a demonstration of using behavior change techniques, feedback and comparison, to promote sustainable travel behavior.