A Traffic Information Fusion Algorithm Based on Self-Organizing Maps

Today with the rapid development of information technology, it is becoming more and more important to be able to share traffic information between various traffic management administrations. The purpose of this paper is to discuss a data fusion algorithm based on Self Organizing Maps (SOMs) for Integrated Traffic Information System (ITIS), which is one of an essential part of Intelligent Transportation Systems (ITS) and is being implemented in many metropolises in China recently. In this paper, the architecture of SOMs network is first described; secondly, the learning and training rules of SOMs are briefly addressed; in the third place, a data fusion algorithm based on SOMs neural network is validated with quantitative traffic data collected on an urban expressway. Through the test in a certain area in the city of Shenzhen, the author obtained the conclusion that the data fusion algorithm studied in this paper can provide precise and comprehensive traffic information in ITIS for travelers and decision-makers, thus improving the safety and efficiency of the surface transportation system.

• Record URL:
  • https://doi.org/10.1061/41184(419)4
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411841
• Supplemental Notes:
  • Copyright © 2011 ASCE
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Bao, Lixia
• Conference:
  • Third International Conference on Transportation Engineering (ICTE)
  • Location: Chengdu , China
  • Date: 2011-7-23 to 2011-7-25
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 19-24
• Monograph Title: ICTE 2011

Subject/Index Terms

• TRT Terms: Advanced traveler information systems; Algorithms; Data fusion; Intelligent transportation systems; Neural networks; Self organizing systems; Traffic data
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I70: Traffic and Transport;

Filing Info

• Accession Number: 01450094
• Record Type: Publication
• ISBN: 9780784411841
• Files: TRIS, ASCE
• Created Date: Oct 23 2012 9:16AM