A NEW TRAFFIC LIGHT SINGLE JUNCTION CONTROL SYSTEM IMPLEMENTED BY A SYMBOLIC NEURAL NETWORK. IN: NEURAL NETWORKS IN TRANSPORT APPLICATIONS

Traffic control systems are traditionally grouped into three main categories: fixed time, flow actuated and vehicle actuated systems. In cases actuated by flow and by traffic, detectors allow, by means of appropriate techniques, detection of flows and/or vehicles traveling on the various links leading to the junction. The paper argues that meny of the control methodologies presented as traffic responsive do not fully meet the requirements. It describes a model developed using a control system implemented by neural networks.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/184014808X
• Corporate Authors:

  Ashgate Publishing Company

  110 Cherry Street, Suite 3-1
  Burlington, VT  United States  05401-3818
• Authors:
  • Burattini, E
  • de Gregorio, M
  • Improta, G
• Publication Date: 1998

Language

• English

Media Info

• Features: Figures; References;
• Pagination: p. 193-209
• Serial:
  • Atmospheric Environment
  • Publisher: Elsevier
  • ISSN: 1352-2310
  • Serial URL: http://www.sciencedirect.com/science/journal/13522310

Subject/Index Terms

• TRT Terms: Artificial intelligence; Intelligent control systems; Intersections; Neural networks; Signalized intersections; Traffic control; Traffic models
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 00796285
• Record Type: Publication
• ISBN: 184014808X
• Files: TRIS
• Created Date: Jul 26 2000 12:00AM