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Generating Road Traffic Information Based on Cellular Network Signaling
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5961-5136
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: urn:nbn:se:liu:diva-87740ISBN: 978-91-7519-693-0 (print)OAI: oai:DiVA.org:liu-87740DiVA: diva2:599856
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
List of papers
1. Generating Road Traffic Information from Cellular Networks - New Possibilities in UMTS
Open this publication in new window or tab >>Generating Road Traffic Information from Cellular Networks - New Possibilities in UMTS
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, Published 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

Keyword
Intelligent Transport Systems, cellular positioning
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-40860 (URN)10.1109/ITST.2006.288805 (DOI)54353 (Local ID)0-7803-9587-5 (ISBN)0-7803-9587-5 (ISBN)54353 (Archive number)54353 (OAI)
Conference
6th International Conference on ITS Telecommunications (ITS-T), June 21-23, Chengdu, China
Available from: 2013-04-05 Created: 2009-10-10 Last updated: 2016-05-04Bibliographically approved
2. Handover location accuracy for travel time estimation in GSM and UMTS
Open this publication in new window or tab >>Handover location accuracy for travel time estimation in GSM and UMTS
2009 (English)In: IET Intelligent Transport Systems, ISSN 1751-956X, E-ISSN 1751-9578, Vol. 3, no 1, 87-94 p.Article in journal (Refereed) Published
Abstract [en]

Field measurements from the GSM and UMTS networks are analysed in a road traffic information context. The measurements indicate a potentially large improvement using UMTS signalling data compared with GSM regarding handover location accuracy. These improvements can be used to generate real-time traffic information with higher quality and extend the geographic usage area for cellular-based travel time estimation systems. The results con. rm previous reports indicating that the technology has a large potential in GSM and also show that the potential might be even larger and more. exible using UMTS. Assuming that non-vehicle terminals can be. ltered out, that vehicles are tracked to the correct route and that handovers can be predicted correctly, a conclusion from the experiments is that the handover location accuracy in both GSM and UMTS will be sufficient to estimate useful travel times, also in urban environments. In a real system, these tasks are typically very challenging, especially in an urban environment. Further, it is reasonably established that the location error will be minor for the data obtained from UMTS.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-16517 (URN)10.1049/iet-its:20070067 (DOI)
Available from: 2013-04-05 Created: 2009-01-30 Last updated: 2016-05-04Bibliographically approved
3. Route Classification in Travel Time Estimation Based on Cellular Network Signaling
Open this publication in new window or tab >>Route Classification in Travel Time Estimation Based on Cellular Network Signaling
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.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-50949 (URN)10.1109/ITSC.2009.5309692 (DOI)978-1-4244-5520-1 (ISBN)978-1-4244-5519-5 (ISBN)
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
4. The Smartphone as Enabler for Road Traffic Information Based on Cellular Network Signalling
Open this publication in new window or tab >>The Smartphone as Enabler for Road Traffic Information Based on Cellular Network Signalling
2012 (English)Manuscript (preprint) (Other academic)
Abstract [en]

The higher penetration rate of GPS-enabled smartphones together with their improved processing power and battery life makes them suitable for a nu mber of participatory sensing applications. The purpose of this paper is to an alyse how GPS-enabled smartphones can be used in a participatory sensingcontext to build a radio map for RSS-based positioning, with a special focus on road traffic information based on cellular network signalling.

The CEP-67 location accuracy achieved is 75 meters for both GSM and UMTS using Bayesian classification. For this test site, the accuracy is similar for GSM and UMTS, with slightly better results for UMTS in the CEP-95 error metric.

The location accuracy achieved is good enough to avoid large errors in travel time estimation for highway environments, especially considering the possibility to filter out estimates with low accuracy using for example the posterior bin probability in Bayesian classification. For urban environments more research is required to determine how the location accuracy will affect the path inference problem in a dense road network. The location accuracy achieved in this paper is also sufficient for other traffic information types, for example origin-destination estimation based on location area updates.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-87739 (URN)
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2016-05-04Bibliographically approved

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