Fan, YinglingWolfson, JulianAdomavicius, GediminasVardhan Das, KirtiKhandelwal, YashKang, Jie2015-07-152015-07-152015-02https://hdl.handle.net/11299/173005The use of mobile phones in collecting travel behavior data has rapidly increased, especially after GPS tracking technology became widely available in commercial smartphones. Existing smartphone-based tools in the field have generally focused on capturing the “when”, “where”, and “how” of travel, i.e., using the smartphone’s automatic sensing functionality to detect travel mode and to collect position and route data. Although locations and modes of transportation derived from sensing data represent important travel behavior information, travel behavior has many other important dimensions—such as trip purpose, travel experience, and travel companionship (i.e., the “why”, “how”, and “who” of travel)—all of which are critical for understanding people’s travel choices. Some of these dimensions may be inferable from pure sensory data, but reliable inference will generally require long-term use data from a very large number of subjects. Other dimensions are simply inaccessible to passive sensing tools. In contrast, traditional travel diary methods and some first-generation smartphone-based travel survey tools enable the collection of multi-dimensional data through high-intensity sampling and qualitative survey techniques. However, these methods are often burdensome to study subjects and impractical for use in a diverse, mobile, and increasingly time-stressed population.enTransportationSmartphoneMobilityDataTravel surveyExperience samplingAccelerometerGPSMode detectionLocation-aware applicationsDestination identificationTrip purposeReport