RegioRail-GNSS Train-Positioning System for Automatic Indications of Crisis Traffic Situations on Regional Rail Lines
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919723" target="_blank" >RIV/00216275:25530/22:39919723 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2076-3417/12/12/5797" target="_blank" >https://www.mdpi.com/2076-3417/12/12/5797</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app12125797" target="_blank" >10.3390/app12125797</a>
Alternative languages
Result language
angličtina
Original language name
RegioRail-GNSS Train-Positioning System for Automatic Indications of Crisis Traffic Situations on Regional Rail Lines
Original language description
The identification of the position of rail vehicles plays a crucial role in the control of rail traffic. Available, up-to-date information on the position of vehicles allows us to efficiently deal with selected traffic situations where the position of vehicles is very important. The main objective of this article is to introduce (i) a concept of a solution for identification of the current position of rail vehicles based on the worldwide-recognized system of the GNSS with the use of an original railway network data model, and (ii) the use of this concept as supplementary support for the dispatcher control of rail traffic on regional lines. The solution was based on an original, multilayer rail network data model supporting (i) the identification of rail vehicle position and (ii) novel algorithms evaluating the mutual positions of several trains while detecting the selected crisis situation. In addition, original algorithms that enable automatic network model-building (on the database server level) directly from the official railway infrastructure database were developed. The verification of the proposed solutions (using rail traffic simulations) was focused on the evaluation of (i) the changing mutual positions (distances) of trains on the railway network, (ii) the detection of nonstandard or crisis traffic situations, and (iii) the results of the calculations of necessary braking distances of trains for stopping and collision avoidance. The above verification demonstrated the good applicability of the proposed solutions for the potential deployment within supplementary software support for real traffic control. The described concept of the supplementary support determined for railway traffic control (using the localization of trains by means of the GNSS) is intended mainly for regional, single-rail lines. This type of line is very often not sufficiently equipped with standard signaling and interlocking equipment to ensure the necessary traffic safety. Therefore, when deploying this support, the new algorithms for the automatic detection of critical traffic situations represent a significant potential contribution to increasing operational safety.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
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
Applied Science - Basel
ISSN
2076-3417
e-ISSN
2076-3417
Volume of the periodical
12
Issue of the periodical within the volume
12
Country of publishing house
CH - SWITZERLAND
Number of pages
23
Pages from-to
nestrankovano
UT code for WoS article
000818285600001
EID of the result in the Scopus database
2-s2.0-85132134174