UrbanMobilitySense: A User-Centric Participatory Sensing System for Transportation Activity Surveys

Abstract

Transportation activity surveys collect the travel behavior of people, including when, where, and how they travel for urban planning purposes. Traditionally, transportation activity surveys are carried out using conventional questionaires, which are labor intensive and error prone. In this paper, we have developed a smartphone-based mobility sensing system, called UrbanMobilitySense, which captures human mobility information automatically to conduct transportation activity surveys. The UrbanMobilitySense system was designed to address two critical issues: 1) energy conservation and 2) privacy preservation. To optimize the energy utilization of smartphone, we avoid using the GPS sensor when the user is at long-stay places and filter out redundant data before data uploading. To preserve personal privacy, each smartphone maintains the user's long-stay places by two separate profiles: 1) private place profile and 2) public place profile. The former maintains the privacy-preserved places (e.g., home), whereas the latter maintains the public places (e.g., parks). We implement the UrbanMobilitySense system to conduct real-world transportation activity surveys, study the performance of our system through extensive experiments, and analyze the computational complexity of the proposed algorithms. The outcome of our work has been deployed in Singapore to support the Land Transport Authority's transportation activity surveys.

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