Analyzing access, egress, and main transport mode of public transit journeys: evidence from the Flemish national household travel survey

The primary objective of this paper is to explore the influence of socio-demographic and contextual variables on the multimodal character of public transit journeys. Accounting for multimodality in public transit journeys is important from a demand modeling point of view, especially in the assessment of new projected public transit infrastructure. To meet the objective, data from the national household travel survey of Flanders (Belgium) is analyzed. Based on 2,202 public transit journeys, the main public transit mode choice (bus/tram/metro or train) and access/egress mode choice are simultane... Mehr ...

Verfasser: CREEMERS, Lieve
BELLEMANS, Tom
JANSSENS, Davy
WETS, Geert
COOLS, Mario
Dokumenttyp: conferenceObject
Erscheinungsdatum: 2015
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-29066240
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://hdl.handle.net/1942/18438

The primary objective of this paper is to explore the influence of socio-demographic and contextual variables on the multimodal character of public transit journeys. Accounting for multimodality in public transit journeys is important from a demand modeling point of view, especially in the assessment of new projected public transit infrastructure. To meet the objective, data from the national household travel survey of Flanders (Belgium) is analyzed. Based on 2,202 public transit journeys, the main public transit mode choice (bus/tram/metro or train) and access/egress mode choice are simultaneously estimated using a multinomial logit model, and by explicitly making a distinction between unimodal and multimodal transit journeys. The results indicate that various socio-demographical (e.g. age, gender, level of education, household income) and contextual factors (e.g. journey distance, journey motive, urbanization degree, car availability) significantly influence the joint decision process. Total journey distance and car availability are identified as the most important explanatory variables. In terms of model performance, the model appears to yield satisfactory predictions, justifying the integration of the model in more general demand modeling frameworks.