The Open UniversitySkip to content

Mining temporal patterns of transport behaviour for predicting future transport usage

Foell, Stefan; Kortuem, Gerd; Rawassizadeh, Reza; Phithakkitnukoon, Santi; Veloso, Marco and Bento, Carlos (2013). Mining temporal patterns of transport behaviour for predicting future transport usage. In: Third International Workshop on Pervasive Urban Applications (PURBA), 8 Sep 2013, Zurich, Switzerland.

Full text available as:
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (237kB) | Preview
Google Scholar: Look up in Google Scholar


There is huge potential in increasing the value of public transportation by creating novel travel information systems which are centred on the individual transport user. Especially, in dense urban cities where it is hard to oversee complex transport networks that are subject to frequent changes, maintenance and construction works, travellers want to be proactively notified about disruptions and traffic incidents relevant to their future behaviour. In this paper, we show how to mine characteristic patterns of the transport routines of urban bus riders for the design of novel travel information system that have the ability to understand forthcoming travel needs of individual users. We leverage on travel histories collected from automated fare collection system (AFC) to extract features of personal transport usage and study their predictive power to forecast whether people access public transport services on a future day or not.

Item Type: Conference or Workshop Item
Copyright Holders: 2013 The Authors
Extra Information: UbiComp '13 Adjunct,
Sept 8-12, 2013,
Zurich, Switzerland.
ISBN: 978-1-4503-2139-6
Keywords: public transport; bus rides; transport usage prediction; automated fare collection data
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Related URLs:
Item ID: 37859
Depositing User: Stefan Foell
Date Deposited: 02 Jul 2013 10:14
Last Modified: 07 Dec 2018 23:03
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU