Combining survey data from different studies to simulate a local travel survey sample data set: an application to the Flemish region

The aim of this paper is enriching the Flemish Household Travel Survey (FHTS) data with local socio-demographic data, available from the National Institute of Statistics (NIS) and further incorporating time-use data, available from the ‘Time-use of the Flemish people’ survey into this framework in order to make more reliable simulations of travel data. The travel attributes to be simulated are examined and households/individuals classified into groups that exhibit similar ranges of selected travel attributes. Using these groupings, distributions of the selected travel attributes are produced,... Mehr ...

Verfasser: NAKAMYA, Juliet
MOONS, Elke
WETS, Geert
Dokumenttyp: conferenceObject
Erscheinungsdatum: 2007
Verlag/Hrsg.: TRB
Schlagwörter: Classification / Data integration / Simulation
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27094381
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://hdl.handle.net/1942/10532

The aim of this paper is enriching the Flemish Household Travel Survey (FHTS) data with local socio-demographic data, available from the National Institute of Statistics (NIS) and further incorporating time-use data, available from the ‘Time-use of the Flemish people’ survey into this framework in order to make more reliable simulations of travel data. The travel attributes to be simulated are examined and households/individuals classified into groups that exhibit similar ranges of selected travel attributes. Using these groupings, distributions of the selected travel attributes are produced, which then become the basis of the simulation. Future research will mainly focus on in-depth validation of the outputs of the simulation process, investigation of the stability of results from different simulation runs and further improvements involving local data updates. It is anticipated that this approach will enable Flanders to develop a local travel data set and estimate travel-demand models at a fraction of the cost of conducting a traditional household travel survey.