Real-Time Freeway Traffic State Estimation Based on Extended Kalman Filter: A Case Study

The authors present a real-time traffic state estimation case study. The authors outline extended Kalman filtering and stochastic macroscopic traffic flow modeling, which form the basis for the adopted general approach to freeway stretch universal traffic state estimators design. Using a 4.1 km Munich, Germany-area freeway stretch, eight hour traffic measurement data was collected for the investigations reported on by the authors. Some of the key issues investigated include biased flow measurement handling capability of the estimator, standard deviation values related noise sensitivity by the estimator, estimated model parameter initial values sensitivity by the estimator, online model parameter estimation significance, and designed traffic state estimator tracking capability. The authors found achieved results quite satisfactory.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767714
• Authors:
  • Wang, Yibing
  • Papageorgiou, Markos
  • Messmer, Albert
• Publication Date: 2007-5

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: pp 167-181
• Serial:
  • Transportation Science
  • Volume: 41
  • Issue Number: 2
  • Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
  • ISSN: 0041-1655
  • Serial URL: http://transci.journal.informs.org/

Subject/Index Terms

• TRT Terms: Case studies; Data files; Estimation theory; Freeways; Kalman filtering; Real time information; Sensitivity; Traffic; Traffic flow; Traffic measurement
• Uncontrolled Terms: Parameters
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01050200
• Record Type: Publication
• Files: TRIS
• Created Date: May 24 2007 3:54PM