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Generating Road Traffic Information from Cellular Networks - New Possibilities in UMTS
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
2006 (English)In: Proceedings 2006 6th International Conference onITS Telecommunications / [ed] Guangjun Wen, Shozo Komaki, Pingzhi Fan and Grabrielle Landrac, 2006, 1128-1133 p.Conference paper (Refereed)
Abstract [en]

This paper summarizes different approaches to collecting road traffic information from second-generation cellular systems (GSM) and point out the possibilities that arise when third generation systems (UMTS) are used. Cell breathing is a potential problem, but smaller cells, soft handover and flexible measurements have the potential to increase the usage area and information quality when road traffic information is extracted from the UMTS network compared to using the GSM network

Place, publisher, year, edition, pages
2006. 1128-1133 p.
Keyword [en]
Intelligent Transport Systems, cellular positioning
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-40860DOI: 10.1109/ITST.2006.288805Local ID: 54353ISBN: 0-7803-9587-5 (online)ISBN: 0-7803-9587-5 (print)OAI: diva2:261709
6th International Conference on ITS Telecommunications (ITS-T), June 21-23, Chengdu, China
Available from: 2013-04-05 Created: 2009-10-10 Last updated: 2013-04-05Bibliographically approved
In thesis
1. Generating Road Traffic Information Based on Cellular Network Signaling
Open this publication in new window or tab >>Generating Road Traffic Information Based on Cellular Network Signaling
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Cellular networks of today generate a massive amount of signalling data. A large part of this signalling is generated to handle the mobility of subscribers, irrespective of the subscriber actively uses the terminal or not. Hence it contains location information that can be used to fundamentally change our understanding of human travel patterns.

This thesis aims to analyse the potential and limitations of using this signalling data in the context of road traffic information, i.e. how we can estimate the road network traffic state based on standard signalling data already available in cellular networks. This is achieved by analytical examination and experiments with signalling data and measurements generated by standard cell phones.

The thesis describes the location data that is available from signalling messages in GSM, GPRS and UMTS networks, both in idle mode and when engaged in a telephone call or a data session. The signalling data available in a ll three networks is useful to estimate traffic information, although the resolution in time and space will to a large extent depend on in which mode the terminal is operating.

Spatial analysis of handover signalling data has been performed for terminals engaged in telephone calls. The analysis indicates that handover events from both GSM and UMTS networks can be used as efficient input to systems for travel time estimation, given that route classification and filtering of non -vehicle terminals can be solved.

By analysing signalling data and received signal strength (RSS) measur ements from cell phones, it can be seen the route classification problem in the context of estimating travel times based on handover events is non -trivial even for highway environments. However, it is presented that the problem can be sa tisfactory solved for highway environments by using basic classification methods, like for example Bayesian classification.

Furthermore the thesis points out that the new era of smartphones can be an enabler for road traffic information from cellular networks in the close future. By examining measurements collected by a smartphone client, it is illu strated how the radio map for cell phone positioning can be built by participatory sensing. It is also shown that the location accuracy of RSS-based cell phone positioning is accurate enough to p rovide both travel time and OD-matrix estimation.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013. 40 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1577
National Category
Engineering and Technology
urn:nbn:se:liu:diva-87740 (URN)978-91-7519-693-0 (ISBN)
2013-01-25, K1, Kåkenhus, Campus Norrköping, Linköpings universitet, Norrköping, 13:15 (English)
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2013-01-22Bibliographically approved

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