The Open UniversitySkip to content

Catch me if you can: predicting mobility patterns of public transport users

Foell, Stefan; Phithakkitnukoon, Santi; Kortuem, Gerd; Veloso, Marco and Bento, Carlos (2014). Catch me if you can: predicting mobility patterns of public transport users. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC 2014), 8-11 Oct 2014, Qingdao, China, IEEE, pp. 1995–2002.

Full text available as:
PDF (Proof) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (2MB) | Preview
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Direct and easy access to public transport information is an important factor for improving the satisfaction and experience of transport users. In the future, public transport information systems could be turned into personalized recommender systems which can help riders save time, make more effective decisions and avoid frustrating situations. In this paper, we present a predictive study of the mobility patterns of public transport users to lay the foundation for transport information systems with proactive capabilities. By making use of travel card data from a large population of bus riders, we describe algorithms that can anticipate bus stops accessed by individual riders to generate knowledge about future transport access patterns. To this end, we investigate and compare different prediction algorithms that can incorporate various influential factors on mobility in public transport networks, e.g., travel distance or travel hot spots. In our evaluation, we demonstrate that by combining personal and population-wide mobility patterns we can improve prediction accuracy, even with little knowledge of past behaviour of transport users.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 IEEE
Project Funding Details:
Funded Project NameProject IDFunding Body
GAMBASNot SetNot Set
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: 40786
Depositing User: Stefan Foell
Date Deposited: 09 Sep 2014 08:23
Last Modified: 01 May 2019 18:55
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

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