FORECASTING URBAN TRAVEL DEMAND FOR QUICK POLICY ANALYSIS WITH DISAGGREGATE CHOICE MODELS: A MONTE CARLO SIMULATION APPROACH

A spatial aggregation methodology based on continuous mathematical functions is employed in urban passenger travel demand prediction. The approach derives aggregate travel demand from disaggregate choice models in the form of multi-dimensional integrals which are solved by Monte Carlo simulation. Approximate empirical relationships are developed to examine the statistical properties of biases and random errors in Monte Carlo prediction. The methodology has been used in developing a comprehensive urban travel demand prediction model suitable for policy-sensitive sketch planning.

  • Availability:
  • Corporate Authors:

    Pergamon Press, Incorporated

    Headington Hill Hall
    Oxford OX30BW,   England 
  • Authors:
    • Watanatada, T
    • Ben-Akiva, Moshe
  • Publication Date: 1979-8

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 00312140
  • Record Type: Publication
  • Source Agency: Engineering Index
  • Files: TRIS
  • Created Date: Jul 22 1981 12:00AM