Measuring uncertainty in discrete choice travel demand forecasting models

Olga Petrik, Filipe Moura and João de Abreu e Silva

Transportation Planning and Technology, 2016, vol. 39, issue 2, 218-237

Abstract: In transportation projects, uncertainty related to the difference between forecast and actual demand is of major interest for the decision-maker, as it can have a substantial influence on the viability of a project. This paper identifies and quantifies discrete choice model uncertainty, which is present in the model parameters and attributes, and determines its impact on risk taking for decision-making applied to a case study of the High-Speed Rail project in Portugal. The methodology includes bootstrapping for the parameter variation, a postulated triangular distribution for the mode-specific input and a probabilistic graphical model for the socio-economic input variation. In comparison to point estimates, the findings for mode shift results in a wider swing in the system, which constitutes valuable information for decision-makers. The methodology, findings and conclusions presented in this study can be generalized to projects involving similar models.

Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1080/03081060.2015.1127542

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