Examples of Validating an Adaptive Kalman Filter Model for Short-Term Traffic Flow Prediction

The paper validates an improved adaptive Kalman filter model (AKFM) for short-term traffic flow prediction on intersections in Shanghai, China. In this field, much research has been conducted in developed countries. However, less work has been done in China, a typical developing country, particularly dealing with the realtime prediction method with mixed traffic flow characteristics. This paper studies the adaptive mechanism method of time-window and the state transition parameters for improved model in detail, and carries out the characteristic and predictability analysis of the traffic flow volume using the detector data of an intersection in Shanghai, China. In addition, this paper has implemented the improved adaptive model in C++ and simulation results show it is effective, stable and self-adaptive. The findings of this study provide some useful insights into the short-term traffic flow prediction in urban intersections or other similar intersections in China.

• Record URL:
  • https://doi.org/10.1061/9780784412442.094
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784412442
• Supplemental Notes:
  • © 2012 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zhang, Liyan
  • Ma, Jian
  • Sun, Jian
• Conference:
  • Twelfth COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2012-8-3 to 2012-8-6
• Publication Date: 2012-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 912-922
• Monograph Title: CICTP 2012: Multimodal Transportation Systems—Convenient, Safe, Cost-Effective, Efficient

Subject/Index Terms

• TRT Terms: Intersections; Kalman filtering; Mathematical prediction; Traffic flow; Validation
• Geographic Terms: Shanghai (China)
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01500618
• Record Type: Publication
• ISBN: 9780784412442
• Files: TRIS, ASCE
• Created Date: Dec 4 2013 11:04AM