Reconstruction of People Flow in Areas of Incomplete Data Availability

Data Assimilation is a technique that synthesizes information from a dynamic (numerical) model and observation data. To reconstruct people flow in areas that are partially invisible to sensors, the authors assess three data assimilation methods: Kalman filter, 3DVAR, and particle filter. While most studies focus on individual-based analysis, in this study, the authors process the movement of people using a dynamic continuum flow theory. The authors derive the dynamic model of people flow and numerically solve it using the data assimilation method. Their proposed method is validated in 1D and 2D simulation experiments and on real tracking data.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 1104-1110
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01604636
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:27PM