Employing Intelligent Algorithms with New Generation Radars

New digital scanning radar technology is making it possible to create a true real time representative image of vehicle and pedestrian behaviour, tagging each moving object with accurate size, location, speed, acceleration, and direction data. This technology has become cost effective and is now easily deployed, and self configuring, providing advanced non intrusive universal traffic sensor. Traffic control algorithms attempt to predict future traffic patterns or conditions by measuring recent past events. The effectiveness of these prediction models depends on the dimensions and resolution at which past events can be measured. The availability of these new advanced radar devices present an opportunity to the traffic engineer to improve control algorithms given the accuracy and richness of the data generated by these advanced radars. These new generation radar sensors promise to revolutionise traffic control systems, by providing non invasive, low cost, mechanisms to collect rich data, prompting traffic engineers to develop new models and systems to solve the challenges of tomorrow.

• Corporate Authors:

  ITS Japan

  Tokyo,   Japan 

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036

  ERTICO

  326 Avenue Louis
  Brussels,   Belgium  B-1050
• Authors:
  • Hall, D C
  • Lamprecht, G
  • Peer, E
  • van der Merwe, H
• Conference:
  • 17th ITS World Congress
  • Location: Busan , Korea, South
  • Date: 2010-10-25 to 2010-10-29
• Publication Date: 2010

Language

• English

Media Info

• Media Type: Digital/other
• Features: Photos; References;
• Pagination: 10p
• Monograph Title: 17th ITS World Congress, Busan, 2010: Proceedings

Subject/Index Terms

• TRT Terms: Algorithms; Radar; Radar vehicle detectors; Real time information; Scanners; Sensors; Traffic control
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01352736
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 28 2011 9:20AM