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Traffic Incident Classification Using Bayesian Approach and Markov Chains

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F15%3A86094055" target="_blank" >RIV/61989100:27740/15:86094055 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.fgg.uni-lj.si/~/sdrobne/sor/SOR'15%20-%20Proceedings.pdf" target="_blank" >http://www.fgg.uni-lj.si/~/sdrobne/sor/SOR'15%20-%20Proceedings.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Traffic Incident Classification Using Bayesian Approach and Markov Chains

  • Original language description

    One of the most challenging parts of the traffic modeling is how to model traffic behavior during traffic incidents. One of the possible approaches to this problem is to use historical data to identify typical incidents and use this knowledge to classifyfuture time series. This classification can be utilized in traffic incident length prediction and analysis. This procedure requires solution to several problems. These problems are how to cluster historic time series, how to parametrize these clusters and how to classify new series. Main aim of this article is to propose solution to the second and the third problem. These methods are called Markov chains and Bayesian classification. Data utilized in this article comes from the RODOS project from CzechRepublic highways.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    SOR '15 proceedings : the 13th International Symposium on Operations Research in Slovenia : Bled, Slovenia, September 23-25, 2015

  • ISBN

    978-961-6165-45-7

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    143-148

  • Publisher name

    Slovenian Society Informatika

  • Place of publication

    Ljubljana

  • Event location

    Bled

  • Event date

    Sep 23, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article