Abstract
This study investigates travel behavior determinants based on a multiday travel survey conducted in the region of Ghent, Belgium. Due to the limited data reliability of the data sample and the influence of outliers exerted on classical principal component analysis, robust principal component analysis (ROBPCA) is employed in order to reveal the explanatory variables responsible for most of the variability. Interpretation of the results is eased by utilizing ROSPCA. The application of ROSPCA reveals six distinct principal components where each is determined by a few variables. Among others, our results suggest a key role of variable categories such as journey purpose-related impedance and journey inherent constraints. Surprisingly, the variables associated with journey timing turn out to be less important. Finally, our findings reveal the critical role of outliers in travel behavior analysis. This suggests that a systematic understanding of how outliers contribute to observed mobility behavior patterns, as derived from travel surveys, is needed. In this regard, the proposed methods serve for processing raw data typically used in activity-based modelling.
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Acknowledgments
The Authors would like to thank the Federal Public Planning Service Science Policy (Belspo) and Dr. Eric Cornelis of FUNDP Namur for providing us with the dataset, and Vlaamse Overheid (IWT-SBO project “Urban Logistics and Mobility”-140433) and Vlaams Instituut voor Mobiliteit (project P081 “Transmob”, IWT ref 140203) for providing funding. Mia Hubert and Pieter Segaert acknowledge Grant C16/15/068 of the Internal Fund KU Leuven.
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Plevka, V., Segaert, P., Tampère, C.M.J. et al. Analysis of travel activity determinants using robust statistics. Transportation 43, 979–996 (2016). https://doi.org/10.1007/s11116-016-9718-2
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DOI: https://doi.org/10.1007/s11116-016-9718-2