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Modelling Occupancy-Queue Relation Using Gaussian Process
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SYSNO ASEP 0506861 Document Type J - Journal Article R&D Document Type The record was not marked in the RIV Subsidiary J Článek ve WOS Title Modelling Occupancy-Queue Relation Using Gaussian Process Author(s) Přikryl, Jan (UTIA-B) RID
Kocijan, J. (SI)Number of authors 2 Source Title Neural Network World. - : Ústav informatiky AV ČR, v. v. i. - ISSN 1210-0552
Roč. 25, č. 1 (2015), s. 35-52Number of pages 18 s. Publication form Print - P Language eng - English Country CZ - Czech Republic Keywords queue estimation ; uncertainty ; traffic model ; Gaussian process Subject RIV BB - Applied Statistics, Operational Research OECD category Statistics and probability R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) MEB091015 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Institutional support UTIA-B - RVO:67985556 UT WOS 000351252000003 EID SCOPUS 84987679930 DOI 10.14311/NNW.2015.25.002 Annotation One 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. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2020
Number of the records: 1