A two-dimensional simulation technique for quantifying the uncertainty of a combined travel demand model

Anthony Chen, S. Pravinvongvuth, P. Chootinan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Uncertainties are unavoidable in the travel demand model. The purpose is to provide a framework for analyzing and quantifying the uncertainty involved in travel demand forecasting models. Instead of using the traditional four-step approach to travel demand modelling that lacks behavioral interpretation and consistency, the combined travel demand model is adopted. A partial linearization algorithm is used for solving this multidimensional travel choice problem. A two-dimensional Monte Carlo simulation technique is proposed to handle the uncertainties. It separately simulates the variability and uncertainty of the combined travel demand model so that individual and collective effects can be better assessed and quantified. Numerical experiment is also conducted to demonstrate the feasibility of the proposed framework.
Original languageEnglish
Title of host publication4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003
PublisherIEEE
Pages367-372
Number of pages6
ISBN (Electronic)0769519970, 9780769519975
DOIs
Publication statusPublished - 1 Jan 2003
Externally publishedYes
Event4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003 - College Park, United States
Duration: 21 Sep 200324 Sep 2003

Conference

Conference4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003
CountryUnited States
CityCollege Park
Period21/09/0324/09/03

Keywords

  • Demand forecasting
  • Employment
  • Feedback
  • Mathematical programming
  • Microeconomics
  • Multidimensional systems
  • Predictive models
  • Transportation
  • Uncertainty

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Control and Optimization
  • Modelling and Simulation

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