Identifying Congestion Patterns in Urban Road Networks Using Floating Car Data

Investigation of congestion patterns in urban road networks based on floating car data (FCD) has shown that noisy and partially incomplete travel speed data from floating cars can be transformed into a consistent and more precise congestion detector value. This value correlates well with measured travel times and observed congestion cases. The method computes local congestion scores, which are averaged and smoothed taking into account information of the actual vehicle paths. The method is able to deal with noisy and missing data. It has been evaluated with measured travel times and automatic congestion detection with video data on a major road in the city of Vienna.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ30 Urban Transportation Data and Information Systems.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Ulm, Michael
  • Heilmann, Bernhard
  • Asamer, Johannes
  • Graser, Anita
  • Ponweiser, Wolfgang
• Conference:
  • Transportation Research Board 94th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2015-1-11 to 2015-1-15
• Date: 2015

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 12p
• Monograph Title: TRB 94th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Algorithms; Floating car data; Incident detection; Methodology; Traffic congestion
• Geographic Terms: Vienna (Austria)
• Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01552860
• Record Type: Publication
• Report/Paper Numbers: 15-1231
• Files: TRIS, TRB, ATRI
• Created Date: Feb 5 2015 1:08PM