A Privacy-Preserving Urban Traffic Estimation System

  • Tian Lei
  • Alexander Minbaev
  • Christian G. ClaudelEmail author
Part of the Complex Networks and Dynamic Systems book series (CNDS, volume 4)


This chapter describes a novel traffic monitoring system based on data generated by Inertial Measurement Units (IMUs) in conjunction with short range Bluetooth or WiFi readers. The IMUs are used to estimate the vehicle path along the transportation network, detect traffic stops and go waves, classify traffic-related events, and possibly monitor the condition of the roadway. We introduce a trajectory estimation method for estimating vehicle paths from IMU data and Bluetooth reader position data only. Using this method, we show that the state of traffic on an urban network can be estimated locally by solving a set of independent traffic estimation problems with unknown boundary conditions. This set of independent solutions are then regularized using a consensus-type algorithm to estimate the unknown boundary conditions during the process. This system allows one to estimate the state of traffic over an urban network, while maintaining the privacy of the users, unlike current systems.



The authors would like to thank the Texas Department of Transportation for supporting this research under project 0-6838, Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Tian Lei
    • 1
    • 2
  • Alexander Minbaev
    • 1
  • Christian G. Claudel
    • 1
    Email author
  1. 1.University of TexasAustinUSA
  2. 2.Chang’an UniversityXi’anChina

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