DEVELOPMENT AND EVALUATION OF A HYBRID TRAVEL TIME FORECASTING MODEL

The aim of this paper was to develop and evaluate a hybrid travel time forecasting model with geographic information systems (GIS) technologies for predicting link travel times in congested road networks. In a prior study (You and Kim, 1999) a non-parametric regression model was developed as a core forecasting algorithm (CFA) to reduce computation time and increase forecasting accuracy. Using the CFA, a prototype hybrid forecasting model was developed and tested by deploying GIS technologies in several different traffic- and road-oriented data environments. This study shows that adopting GIS technologies in link travel time forecasting is efficient for achieving the reduction of computational delay and increasing forecasting accuracy.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Corporate Authors:

  Elsevier

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  Kidlington, Oxford  United Kingdom  OX5 1GB
• Authors:
  • You, J
  • Kim, T J
• Publication Date: 2000-2

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 231-256
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 8
  • Issue Number: 1
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Algorithms; Databases; Forecasting; Geographic information systems; Highway transportation; Hybrid simulation; Nonparametric analysis; Traffic congestion; Traffic data; Travel time
• Uncontrolled Terms: Road networks
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 00800327
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Oct 4 2000 12:00AM