In the urban travel demand forecasting process, the modal share can be determined by using either aggregate or disaggregate models. Disaggregate models have two main advantages over aggregate models. The first advantage is that they can explain the individual's trip choices in terms of human travel behavior. The second advantage is that they can guide the decision maker in analyzing the effects of certain policy decisions on the travel demand by various modes. The successful use of disaggregate models, however, depends upon reaching minimal aggregation error during the process of transforming disaggregate choices to aggregate travel demand. The main emphasis of this paper is on the application of disaggregate modal choice models for aggregate demand prediction and for policy decisions and not on disaggregate model development. The latter has been discussed in a previous paper by the authors. Using the multimodal choice model developed for the city of Toronto, this paper shows that reasonable results can be obtained while aggregating the disaggregate models for prediction purposes. Minimal aggregation error is achieved using the technique of "segmentation of population into groups". The results are presented both for the observations used in developing the model and for observations outside the sample area, thus providing an insight into the accuracy of the aggregation procedure. The paper also demonstrates by examples how the disaggregate modal choice model can be used as a policy analysis tool. /Author/TRRL/

  • Corporate Authors:

    University of British Columbia, Vancouver

    Faculty of Commerce
    Vancouver, British Columbia  Canada 
  • Authors:
    • Cherian, V
    • Sargious, M
    • MORRALL, J
  • Publication Date: 1977


  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 00168134
  • Record Type: Publication
  • Source Agency: Transport and Road Research Laboratory (TRRL)
  • Files: ITRD, TRIS
  • Created Date: Jun 28 1981 12:00AM