Citation

Servizi V, Pereira FC, Anderson MK, Nielsen OA. Eur. Transp. Res. Rev. 2021; 13(1): e57.

Copyright

(Copyright © 2021, European Conference of Transport Research Institutes, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1186/s12544-021-00516-z

PMID

unavailable

Abstract

Although people and smartphones have become almost inseparable, especially during travel, smartphones still represent a small fraction of a complex multi-sensor platform enabling the passive collection of users' travel behavior. Smartphone-based travel survey data yields the richest perspective on the study of inter- and intrauser behavioral variations. Yet after over a decade of research and field experimentation on such surveys, and despite a consensus in transportation research as to their potential, smartphone-based travel surveys are seldom used on a large scale.

Language: en

Keywords

Activity inference; Data fusion; Machine learning; Map-matching; Mode detection; Smartphone-based travel surveys; Transport; User behavior