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Route Classification in Travel Time Estimation Based on Cellular Network Signaling
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology. (Mobil telekommunikation)ORCID iD: 0000-0002-5961-5136
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology. (Mobil telekommunikation)
2009 (English)In: Proceedings of 12th International IEEE Conference on Intelligent Transport Systems (ITSC), October 3-7, St. Louis, USA, 2009, 474-479 p.Conference paper, Published paper (Refereed)
Abstract [en]

Travel time estimation based on cellular network signaling is a promising technology for delivery of wide area travel times in real-time. The technology has received much attention recently, but few academic research reports has so far been published in the area, which together with uncertain location estimates and environmental dependent performance makes it difficult to assess the potential of the technology. This paper aims to investigate the route classification task in a cellular travel time estimation context in detail. In order to estimate the magnitude of the problem, two classification algorithms are developed, one based on nearest neighbor classification and one based on Bayesian classification. These are then evaluated using field measurements from the GSM network. A conclusion from the results is that the route classification problem is not trivial even in a highway environment, due to effects of multipath propagation and changing radio environment. In a highway environment the classification problem can be solved rather efficiently using e.g., one of the methods described in this paper, keeping the effect on travel time accuracy low. However, in order to solve the route classification task in urban environments more research is required.

Place, publisher, year, edition, pages
2009. 474-479 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-50949DOI: 10.1109/ITSC.2009.5309692ISBN: 978-1-4244-5520-1 (print)ISBN: 978-1-4244-5519-5 (print)OAI: oai:DiVA.org:liu-50949DiVA: diva2:272382
Conference
12th International IEEE Conference on Intelligent Transport Systems (ITSC), October 3-7, St. Louis, USA
Available from: 2013-04-05 Created: 2009-10-15 Last updated: 2016-05-04Bibliographically 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.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1577
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-87740 (URN)978-91-7519-693-0 (ISBN)
Presentation
2013-01-25, K1, Kåkenhus, Campus Norrköping, Linköpings universitet, Norrköping, 13:15 (English)
Opponent
Supervisors
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2016-05-04Bibliographically approved

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Gundlegård, DavidKarlsson, Johan M

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