Novel Road Classifications for Large Scale Traffic Networks

Werner Toplak, Hannes Koller, Melitta Dragaschnig, Dietmar Bauer, Johannes Asamer (Speaker)

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review


Establishing a highly sophisticated large-scale Traffic Information System (TIS) requires the creation and deployment of link travel time prediction models for large road networks. Due to the dimension of typical road networks and low coverage with Floating Cars (FC), data sets that can be used for prediction contain a large number of missing observations. Additionally, specifying prediction models for each link separately is impossible due to restrictions of both computational as well as modeling resources. This paper aims to improve the scalability of link travel time predictions by combining information from roads with similar characteristics. The Functional Road Class (FRC) is a widely accepted indicator for road similarity mainly based on static information from infrastructure planning. The coherence between the clustering introduced by the FRC and road dynamics measured by Floating Car Data (FCD) in the city of Vienna is discussed and analyzed. Clustering approaches that are based on indices characterizing speed measurement distributions are proposed as alternatives to the FRC system. It is demonstrated by way of examples that the new clustering is much more appropriate to provide predictions of link travel times.
Original languageEnglish
Title of host publicationITSC 2010 Conference Proceedings
Publication statusPublished - 2010
Event13th International IEEE Conference on Intelligent Transportation Systems -
Duration: 19 Sept 201022 Sept 2010


Conference13th International IEEE Conference on Intelligent Transportation Systems

Research Field

  • Former Research Field - Mobility Systems


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