In the Russian Federation, most railway accidents take place at unguarded railway crossings. The majority of scientific papers on the topic of crossings deal with the improvement of guarded railway crossings operation. At present, there is no effective way to improve safety at unguarded railway crossings. The subject of the study is unguarded railway crossings. The aim of the paper is to develop a set of preventive measures to avoid accidents at unguarded railway crossings. The article describes the cases of traffic accidents at railway crossings of the West Siberian railway, studies the scheme of unguarded railway crossings and offers a schematic diagram of the accident prevention system at unguarded railway crossings. The work algorithm of the accident prevention system at unguarded railway crossings and the algorithm of giving the locomotive a notification of an emergency situation at unguarded railway crossings are presented. Using the existing coding scheme of the automatic continuous locomotive signaling as a transmission line for information about an emergency situation at a railway crossing allows simplifying significantly the scheme of the developed system. The paper also calculates the maximum permissible time of occupation of the crossing by motor vehicles and the time of coding change in the automatic locomotive signaling system of continuous type. The proposed accident prevention system at unguarded railway crossings does not require additional equipment to organize the communication channel and is cost-neutral. Equipping unguarded railway crossings with this system will improve train safety, reduce the number of accidents and increase the efficiency of the railway transport complex in general.


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    Titel :

    Accident Prevention System at Unguarded Railway Crossings


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Guda, Alexander (Herausgeber:in) / Akhmedzyanov, Gayaz (Autor:in) / Dremin, Vladimir (Autor:in) / Litvinov, Artem (Autor:in)

    Kongress:

    International School on Neural Networks, Initiated by IIASS and EMFCSC ; 2022 ; St.Petersburg, Russia February 08, 2022 - February 10, 2022



    Erscheinungsdatum :

    16.11.2022


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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