SHORT-TERM TRAFFIC FORECASTING: OVERVIEW OF OBJECTIVES AND METHODS

In the last two decades, the growing need for short-term prediction of traffic parameters embedded in a real-time intelligent transportation systems environment has led to the development of a vast number of forecasting algorithms. Despite this, there is still not a clear view about the various requirements involved in modelling. This field of research was examined by disaggregating the process of developing short-term traffic forecasting algorithms into three essential clusters: the determination of the scope, the conceptual process of specifying the output and the process of modelling, which includes several decisions concerning the selection of the proper methodological approach, the type of input and output data used, and the quality of the data. A critical discussion clarifies several interactions between the above and results in a logical flow that can be used as a framework for developing short-term traffic forecasting models. (A)

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/7802200
• Corporate Authors:

  Taylor & Francis

  4 Park Square, Milton Park
  Abingdon,   United Kingdom  OX14 4RN
• Authors:
  • Vlahogianni, E I
  • Golias, J C
  • Karlaftis, M G
• Publication Date: 2004-9

Language

• English

Media Info

• Features: References;
• Pagination: p. 533-57
• Serial:
  • Transport Reviews
  • Volume: 24
  • Issue Number: 5
  • Publisher: Routledge
  • ISSN: 0144-1647
  • EISSN: 1464-5327
  • Serial URL: http://www.tandfonline.com/loi/ttrv20

Subject/Index Terms

• TRT Terms: Calculation; Data collection; Forecasting; Intelligent transportation systems; Mathematical models; Methodology; Traffic; Traffic control
• ITRD Terms: 6464: Calculation; 8623: Data acquisition; 132: Forecast; 8735: Intelligent transport system; 6473: Mathematical model; 9102: Method; 755: Traffic; 654: Traffic control
• Subject Areas: Operations and Traffic Management;

Filing Info

• Accession Number: 00979682
• Record Type: Publication
• Source Agency: Transport Research Laboratory
• Files: ITRD, ATRI
• Created Date: Oct 6 2004 12:00AM