Incident Detection from Cellular Network Signalling

This paper presents a system that is able to detect incidents and predict travel times on main traffic roads by monitoring the movement patterns of cellular network devices. The authors show that abnormal road traffic conditions map to anomalies in the network mobility signalling. By properly analysing these anomalies, it is possible to (i) measure short-distance travel times, which in turn can be used for incident detection, and (ii) predict long-distance travel times based on current traffic conditions. By means of a field-test we demonstrate how a system based exclusively on cellular network data can complement and improve existing solutions for road traffic monitoring.

• Supplemental Notes:
  • Abstract reprinted with permission from Intelligent Transportation Society of America.
• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Janecek, A
  • Valerio, D
  • Ruehrup, S
  • Hummel, K A
  • Hlavacs, H
  • Ricciato, F
  • Rainer, B
  • Mullner, W
• Conference:
  • 19th ITS World Congress
  • Location: Vienna , Austria
  • Date: 2012-10-22 to 2012-10-26
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Features: CD-ROM; Figures; Maps; References;
• Pagination: 6p
• Monograph Title: 19th ITS World Congress, Vienna, Austria, 22 to 26 October 2012

Subject/Index Terms

• TRT Terms: Incident detection; Traffic data; Traffic signal control systems; Traffic surveillance; Travel patterns; Travel time
• Uncontrolled Terms: Long distance travel; Traffic conditions
• Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01496483
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 24 2013 3:38PM