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Tracking travel patterns and modes is a goal that is useful on many levels, including calculating the transportation emissions of a population. Prior efforts to collect this information have been stymied by low accuracies or reliance on supplementary devices. In this paper, we describe a system that improves accuracy by using prompted recall on the smartphone, and aggregates the information to help detect large scale patterns. We also present the evaluation of a prototype implementation that was used to collect data from 44 users in the San Francisco Bay Area over 3 months.

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