Supervised learning

Predicting passenger load in public transport

Conference Paper (2018)
Author(s)

L.J.C. Heydenrijk-Ottens (TU Delft - Transport and Planning)

V. Degeler (TU Delft - Transport and Planning)

Ding Luo (TU Delft - Transport and Planning)

Niels van Van Oort (TU Delft - Transport and Planning)

Hans Lint (TU Delft - Transport and Planning)

Research Group
Transport and Planning
Copyright
© 2018 L.J.C. Heydenrijk-Ottens, V. Degeler, D. Luo, N. van Oort, J.W.C. van Lint
More Info
expand_more
Publication Year
2018
Language
English
Copyright
© 2018 L.J.C. Heydenrijk-Ottens, V. Degeler, D. Luo, N. van Oort, J.W.C. van Lint
Research Group
Transport and Planning
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

In this extended abstract, we show the supervised learning approach to
predicting passenger load of trams, based on historical passenger load patterns. We look at two different cases: predicting long-term passenger load of any given day and time, and predicting short-term passenger load at a particular public transport vehicle.

Files

CASPT_2018_paper_76.pdf
(pdf | 1.15 Mb)
License info not available