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Demonstration of Smart Railway Level Crossing Design and Validation Using Data from Metro Rail, South Africa

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919628" target="_blank" >RIV/00216275:25530/22:39919628 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.hindawi.com/journals/jat/2022/6614242/" target="_blank" >https://www.hindawi.com/journals/jat/2022/6614242/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1155/2022/6614242" target="_blank" >10.1155/2022/6614242</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Demonstration of Smart Railway Level Crossing Design and Validation Using Data from Metro Rail, South Africa

  • Original language description

    Long waiting time at railway level crossings poses a risk on the safety and affects capacity of rail and road traffic. However, in most cases, the long closing time can be prevented by reducing the time lost at a railway level crossing. The emphasis of this study is to present a numerical optimisation algorithm to reduce the time lost per train trip at a railway level crossing. Thus, attributes with the highest impact on the railway level crossing closing time were extracted from the data analysis of rail-road level crossings on the southern corridor of the Western Cape metro rail. Powell&apos;s optimisation algorithm was formulated on the minimisation of the time lost at the railway level crossing per trip. Thus, time lost is constrained by the technical and train&apos;s traction constraints. The upper and lower bounds of Powell&apos;s algorithm were defined by the threshold closing time in addition to the actual and expected probability density functions. The algorithm was implemented in Matlab. Furthermore, the algorithm was trained on 8000 data sets and tested on 2000 data sets. The developed algorithm proved to be effective and robust in comparison to the current state of railway level crossings under study. Thus, the algorithm was validated to reduce the time lost at the railway level crossing by at least 50%.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20104 - Transport engineering

Result continuities

  • Project

    <a href="/en/project/EF17_049%2F0008394" target="_blank" >EF17_049/0008394: Cooperation in Applied Research between the University of Pardubice and companies, in the Field of Positioning, Detection and Simulation Technology for Transport Systems (PosiTrans)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Journal of Advanced Transportation

  • ISSN

    0197-6729

  • e-ISSN

    2042-3195

  • Volume of the periodical

    2022

  • Issue of the periodical within the volume

    February

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    10

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000774326600002

  • EID of the result in the Scopus database