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Quantifying uncertainties in a national forecasting model
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.ORCID iD: 0000-0002-4754-3147
2005 (English)In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, Vol. 39, no 6, 531-547 p.Article in journal (Refereed) Published
Abstract [en]

Uncertainties related to demand model system outputs is an important issue in travel demand models. This paper focuses on uncertainties arisen from the fact that models are estimated on a sample of the population (and not the whole population). Forecasting systems can be quite complex, and may contain procedures that not easily permit analytically derived statistical measures of uncertainty. In this paper, the possibilities to use computer-intensive numerical methods to compute statistical measures for very complex systems, without being bound to an analytical approach, are explored. Here, the bootstrap method is used to obtain statistical measures of outputs produced by the forecasting system SAMPERS. The SAMPERS system is used by Swedish transport authorities. The bootstrap method is briefly described as well as the procedure of applying bootstrap on the SAMPERS system. Numerical results are presented for selected forecast results at different levels such as total traffic demand, origin-destination demand, train line demand and the demand on specific links. Also, the uncertainty related to the value of time estimate is analysed. 

Place, publisher, year, edition, pages
2005. Vol. 39, no 6, 531-547 p.
Keyword [en]
travel demand, bootstrap, computer-intensive statistical method, SAMPERS
National Category
Transport Systems and Logistics
URN: urn:nbn:se:kth:diva-71385DOI: 10.1016/j.tra.2005.02.010ISI: 000229420300004OAI: diva2:486716
TSC import 359 2012-01-30. QC 20120202Available from: 2012-01-31 Created: 2012-01-31 Last updated: 2012-02-02Bibliographically approved

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Beser Hugosson, Muriel
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