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dc.contributor.authorSteiner, Albert-
dc.contributor.authorHosang, Jürg-
dc.contributor.authorMeierhofer, Jürg-
dc.date.accessioned2018-05-25T07:58:56Z-
dc.date.available2018-05-25T07:58:56Z-
dc.date.issued2004-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/6092-
dc.description.abstractTraffic and traffic congestions in particular have an increasing economic impact at a national as well as a regional level. Data available from surveys performed on the Swiss freeway network show a surge in the accumulated yearly hours of congestion between the years 1994 and 2003. Congestions have different causes. However, the three major reasons identified are capacity overloads, incidents and temporary building sites where mainly the capacity overloads had a strong increase over the last years. Therefore, the focus of this paper is on this topic. In this paper, we present two data analysis methods, which are applied to vehicular traffic data. The goal of the first method is to estimate link travel times based on a re-identification algorithm applied on single vehicle data. The second approach seeks for incident detection using discrete wavelet transformation (DWT) technique. Both methods are implemented within a MATLAB®-environment and are intended to be a basis for other, superior algorithms to be developed for “Intelligent Transportation Systems (ITS)”. Their feasibility as well as their benefit is shown using real data. Moreover, a comparison of the estimated points in time of the beginning and the end of the congestion observed is conducted. The results show good consistence and thus represent a promising basis for further research on these topics.de_CH
dc.language.isoende_CH
dc.publisherIPLnetde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectVerkehrde_CH
dc.subjectPattern recognitionde_CH
dc.subjectWaveletde_CH
dc.subject.ddc380: Verkehrde_CH
dc.titleVehicular traffic data analysis and its benefits to prevent traffic congestionde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.conference.detailsIPLnet 2004 Workshop, Automation and logistics for manufacturing in Switzerland, Murten, 7-8 September 2004de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
zhaw.title.proceedingsProceedings of the IPLnet 2004 Workshopde_CH
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Steiner, A., Hosang, J., & Meierhofer, J. (2004). Vehicular traffic data analysis and its benefits to prevent traffic congestion. Proceedings of the IPLnet 2004 Workshop.
Steiner, A., Hosang, J. and Meierhofer, J. (2004) ‘Vehicular traffic data analysis and its benefits to prevent traffic congestion’, in Proceedings of the IPLnet 2004 Workshop. IPLnet.
A. Steiner, J. Hosang, and J. Meierhofer, “Vehicular traffic data analysis and its benefits to prevent traffic congestion,” in Proceedings of the IPLnet 2004 Workshop, 2004.
STEINER, Albert, Jürg HOSANG und Jürg MEIERHOFER, 2004. Vehicular traffic data analysis and its benefits to prevent traffic congestion. In: Proceedings of the IPLnet 2004 Workshop. Conference paper. IPLnet. 2004
Steiner, Albert, Jürg Hosang, and Jürg Meierhofer. 2004. “Vehicular Traffic Data Analysis and Its Benefits to Prevent Traffic Congestion.” Conference paper. In Proceedings of the IPLnet 2004 Workshop. IPLnet.
Steiner, Albert, et al. “Vehicular Traffic Data Analysis and Its Benefits to Prevent Traffic Congestion.” Proceedings of the IPLnet 2004 Workshop, IPLnet, 2004.


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