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Uncertainty in traffic forecasts: literature review and new results for The Netherlands

  • Gerard Jong


  • Andrew Daly
  • Marits Pieters
  • Stephen Miller
  • Ronald Plasmeijer
  • Frank Hofman
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    This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty in traffic forecasts in The Netherlands. Copyright Springer Science+Business Media, LLC 2007

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    Article provided by Springer in its journal Transportation.

    Volume (Year): 34 (2007)
    Issue (Month): 4 (July)
    Pages: 375-395

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    Handle: RePEc:kap:transp:v:34:y:2007:i:4:p:375-395
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    1. Andrew Daly & James Fox & Jan Gerrit Tuinenga, 2005. "Pivot-Point Procedures in Practical Travel Demand Forecasting," ERSA conference papers ersa05p784, European Regional Science Association.
    2. Rodier, Caroline J. & Johnston, Robert A., 2002. "Uncertain socioeconomic projections used in travel demand and emissions models: could plausible errors result in air quality nonconformity?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(7), pages 613-631, August.
    3. Yong Zhao & Kara Maria Kockelman, 2002. "The propagation of uncertainty through travel demand models: An exploratory analysis," The Annals of Regional Science, Springer, vol. 36(1), pages 145-163.
    4. Hugosson, Muriel Beser, 2005. "Quantifying uncertainties in a national forecasting model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(6), pages 531-547, July.
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