Trip chaining impact on within-day mode choice dynamics: Evidences from a multi-day travel survey | Zendy

Ariane Scheffer | Zendy; Richard D. Connors | Zendy; Francesco Viti | Zendy

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Trip chaining impact on within-day mode choice dynamics: Evidences from a multi-day travel survey

Author(s) -

Ariane Scheffer,

Richard D. Connors,

Francesco Viti

Publication year - 2021

Publication title -

transportation research procedia

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.657

H-Index - 40

eISSN - 2352-1465

pISSN - 2352-1457

DOI - 10.1016/j.trpro.2021.01.082

Subject(s) - mode choice , mode (computer interface) , chaining , modal , computer science , econometrics , travel behavior , geography , transport engineering , statistics , operations research , mathematics , engineering , psychology , public transport , chemistry , polymer chemistry , psychotherapist , operating system

Mode choice is influenced by a large variety of factors, as for example users’ socio-economic attributes or level of service for the different alternatives. In order to understand better what leads to temporal and spatial variations of modal split, we propose in this paper an analysis of a multi-day travel survey, with a series of descriptive statistics as well as inferential analysis on the correlation between mode choice and tour-specific attributes at both spatial and temporal levels. This paper discusses the importance of considering tour-based mode choice not only because it brings consistency between successive mode choices but also allows the inclusion of relevant tours’ characteristics such as activity types, distances, time of the day, and previous mode choices. A total of 5848 home-based tours done in 2008 are studied in the area of Ghent, Belgium. Identified patterns show the importance of modelling dynamic mode choice with trip chaining and time of the day. The modal share of car drivers differs of more than 40% between hours of the day and about 30% between different activities. Furthermore, the definition of activity spaces by principal mode choice and home-work locations introduces the calibration of probabilistic aggregate Gaussian fit to visited points.

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