A Mixed AHP-ANN Method to Determine Toll Rate Coefficient

Different toll rate coefficients should reflect different pricing for different vehicle class users, in order to achieve equality of cost and profits. This article reports on a model that takes into account both objective and subjective factors, to establish a road cost and user profits index system. The authors use analytic hierarchy process and BP neural networks to determine toll rate coefficients. Experiments using this model demonstrate that the results are reasonable, feasible, and useful in a real world setting.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/10062823
• Authors:
  • Xiangyang, He
  • Qingnian, Zhang
  • Tao, Ding
• Publication Date: 2007-2

Language

• English

Media Info

• Media Type: Print
• Features: References;
• Pagination: pp 137-179
• Serial:
  • Journal of Wuhan University of Technology: Transportation Science & Engineering
  • Volume: 31
  • Issue Number: 1
  • Publisher: Wuhan University of Technology
  • ISSN: 1006-2823

Subject/Index Terms

• TRT Terms: Costs; Highway traffic; Neural networks; Profits; Rates, fares and tolls; Tolls; Vehicle classification
• Subject Areas: Finance; Highways; Operations and Traffic Management; Planning and Forecasting; I10: Economics and Administration; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01081454
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 28 2007 8:26AM