Virtual trip lines for distributed privacy-preserving traffic monitoring

  • Authors:

  • Baik Hoh;Marco Gruteser;Ryan Herring;Jeff Ban;Daniel Work;Juan-Carlos Herrera;Alexandre M. Bayen;Murali Annavaram;Quinn Jacobson

  • Affiliations:

  • Rutgers University, Piscataway, NJ, USA;Rutgers University, Piscataway, NJ, USA;UC Berkeley, Berkeley, CA, USA;California Center for Innovative Transportation, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;USC, Los Angeles, CA, USA;Nokia Research Center, Palo Alto, CA, USA

  • Venue:
  • Proceedings of the 6th international conference on Mobile systems, applications, and services
  • Year:
  • 2008

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Abstract

Automotive traffic monitoring using probe vehicles with Global Positioning System receivers promises significant improvements in cost, coverage, and accuracy. Current approaches, however, raise privacy concerns because they require participants to reveal their positions to an external traffic monitoring server. To address this challenge, we propose a system based on virtual trip lines and an associated cloaking technique. Virtual trip lines are geographic markers that indicate where vehicles should provide location updates. These markers can be placed to avoid particularly privacy sensitive locations. They also allow aggregating and cloaking several location updates based on trip line identifiers, without knowing the actual geographic locations of these trip lines. Thus they facilitate the design of a distributed architecture, where no single entity has a complete knowledge of probe identities and fine-grained location information. We have implemented the system with GPS smartphone clients and conducted a controlled experiment with 20 phone-equipped drivers circling a highway segment. Results show that even with this low number of probe vehicles, travel time estimates can be provided with less than 15% error, and applying the cloaking techniques reduces travel time estimation accuracy by less than 5% compared to a standard periodic sampling approach.