Number of the records: 1  

Modelling Occupancy-Queue Relation Using Gaussian Process

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    SYSNO ASEP0506861
    Document TypeJ - Journal Article
    R&D Document TypeThe record was not marked in the RIV
    Subsidiary JČlánek ve WOS
    TitleModelling Occupancy-Queue Relation Using Gaussian Process
    Author(s) Přikryl, Jan (UTIA-B) RID
    Kocijan, J. (SI)
    Number of authors2
    Source TitleNeural Network World. - : Ústav informatiky AV ČR, v. v. i. - ISSN 1210-0552
    Roč. 25, č. 1 (2015), s. 35-52
    Number of pages18 s.
    Publication formPrint - P
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsqueue estimation ; uncertainty ; traffic model ; Gaussian process
    Subject RIVBB - Applied Statistics, Operational Research
    OECD categoryStatistics and probability
    R&D Projects1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    MEB091015 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    Institutional supportUTIA-B - RVO:67985556
    UT WOS000351252000003
    EID SCOPUS84987679930
    DOI10.14311/NNW.2015.25.002
    AnnotationOne of the key indicators of the quality of service for urban transportation control systems is the queue length. Even in unsaturated conditions, longer queues indicate longer travel delays and higher fuel consumption. With the exception of some expensive surveillance equipment, the queue length itself cannot be measured automatically, and manual measurement is both impractical and costly in a long term scenario. Hence, many mathematical models that express the queue length as a function of detector measurements are used in engineering practice, ranging from simple to elaborate ones. The method proposed in this paper makes use of detector time-occupancy, a complementary quantity to vehicle count, provided by most of the traffic detectors at no cost and disregarded by majority of existing approaches for various reasons. Our model is designed as a complement to existing methods. It is based on Gaussian-process model of the occupancy-queue relationship, it can handle data uncertainties, and it provides more information about the quality of the queue length prediction.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2020
Number of the records: 1  

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