Future Mobility Sensing (FMS) is a smartphone-based travel survey system that employs a web-based prompted-recall interaction to correct automatically inferred information. A key component of FMS is a stop detection algorithm that derives the users’ activity locations and times based on the raw data collected by their phones. Output of this algorithm is presented in the Activity Diary for the users to validate, and its accuracy has a significant impact on user burden. In this paper, we present FMS’ stop detection algorithm and its performance during testing by volunteers and public users during a large-scale field test.
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