Lagrangian sensing: Traffic estimation with mobile devices

Daniel Work, Olli Pekka Tossavainen, Quinn Jacobson, Alexandre M. Bayen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An inverse modeling algorithm is developed to reconstruct the state of traffic (velocity field) on highways from GPS measurements gathered from mobile phones traveling on-board vehicles. The algorithm is based on ensemble Kalman filtering (EnKF), to overcome the nonlinearity and non-differentiability of a distributed highway traffic model for velocity. The algorithm is implemented in an architecture which includes GPS enabled phones and a privacy aware data collection infrastructure based on the novel concept of Virtual Trip Lines (a technology developed by Nokia). The data collection infrastructure is connected to a traffic estimation server running the EnKF algorithm online, and the estimation results are broadcast in real time back to mobile phones and to the internet. Results from the algorithm are presented using data collected during the February 8, 2008 Mobile Century experiment, in which a shock wave from a five-car accident is captured. A prototype estimation algorithm and system were run during the experiment, and highlight that measurements from as few as 2% to 5% of the commuting public are sufficient to accurately reconstruct the highway traffic state.

Original languageEnglish (US)
Title of host publication2009 American Control Conference, ACC 2009
Pages1536-1543
Number of pages8
DOIs
StatePublished - Nov 23 2009
Event2009 American Control Conference, ACC 2009 - St. Louis, MO, United States
Duration: Jun 10 2009Jun 12 2009

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2009 American Control Conference, ACC 2009
CountryUnited States
CitySt. Louis, MO
Period6/10/096/12/09

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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