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Backcasting in freight transport demand modelling – chances and challenges

Lange, Peter and Huber, Stefan (2015) Backcasting in freight transport demand modelling – chances and challenges. [Other]

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Freight transport demand models are important tools to support policy decision-making by enabling decision makers to evaluate transport policies and correlated effects. This significance puts high pressure on freight models regarding their accuracy. In order to ensure model accuracy there are different methods within the wide area of quality assurance that can be applied. Although backcasting is such a method it is, however, often neglected or implemented insufficiently. The paper presents major challenges and chances occurring from backcasting that have been conducted using a state-of-the- practise freight model. It reveals that backcasting is not easy to handle – especially referring to data availability and quality. Serious challenges emerge regarding availability of consistent input and output data as well as goods classification. A guideline, deduced from the experience in application, is presented to assist practising backcasting in freight modelling.

Item URL in elib:https://elib.dlr.de/98068/
Document Type:Other
Additional Information:Working Paper
Title:Backcasting in freight transport demand modelling – chances and challenges
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Huber, Stefanstefan.huber (at) dlr.deUNSPECIFIED
Date:September 2015
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:freight transport demand modelling; backcasting
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Verkehrsentwicklung und Umwelt II (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transport Research > Commercial Transport
Deposited By: Huber, Stefan
Deposited On:19 Nov 2015 14:55
Last Modified:31 Jul 2019 19:54

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