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Exploring synergy relationships between telematic services and functionalities using cluster analysis
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-9471-8405
Malmö högskola, Faculty of Technology and Society (TS). Malmö högskola, Internet of Things and People (IOTAP).ORCID iD: 0000-0003-0998-6585
2015 (English)In: IET Intelligent Transport Systems, ISSN 1751-956X, E-ISSN 1751-9578, Vol. 9, no 4, p. 366-374Article in journal (Refereed)
Abstract [en]

A method for assessing potential synergies among different sets of transport telematic services (TTSs) is suggested. An Intelligent Transport System enhances transport by delivering one or more TTSs. The ability to deliver multiple TTSs to address a wide range of stakeholder needs is gaining momentum, not only from a marketing perspective but also from a technological perspective. The total cost of TTSs can be reduced if they share functionalities (i.e., sub-services provided by telematic systems). We show how this synergy can be assessed with the help of clustering methods. Knowledge about possible synergies of functionalities is useful in the (re)design and eventual deployment of TTSs, especially when the underlying telematic systems are able to support multiple TTSs. To adapt the clustering method for this purpose, we suggest a mathematical formulation of synergy among functionalities of TTSs. By applying the method to a set of 32 TTSs, we obtain a cluster formation of these TTSs according to their synergy measures. Overall, the results suggest that the joint implementation of TTSs targeted toward some problem domains can lead to significant cost savings, for example, Road User Charging, Infrastructure Repair and Maintenance, and Information on the Transport of extra large goods for the management of road transport infrastructure.

Place, publisher, year, edition, pages
Institution of Engineering and Technology (IET) , 2015. Vol. 9, no 4, p. 366-374
Keywords [en]
Telematic services, Intelligent transport systems, Cluster analysis
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-2382DOI: 10.1049/iet-its.2014.0049ISI: 000354468200003Scopus ID: 2-s2.0-84929377392Local ID: 18671OAI: oai:DiVA.org:mau-2382DiVA, id: diva2:1399135
Available from: 2020-02-27 Created: 2020-02-27 Last updated: 2024-02-06Bibliographically approved

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Persson, Jan A.Davidsson, Paul

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