Open AccessBlockchain‐enabled virtual coupling of automatic train operation fitted mainline trains for railway traffic conflict control
Author(s) -
Muniandi Ganesan
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0694
Subject(s) - train , control (management) , computer science , coupling (piping) , real time computing , transport engineering , automotive engineering , engineering , artificial intelligence , geography , cartography , mechanical engineering
Railway traffic conflicts are common in the day‐to‐day operation of trains due to the limited track capacity, the varying priority of trains, localised weather conditions, maintenance operations etc. The conventional conflict resolution strategy focuses on delaying the trains by considering the braking distance of a preceding train, cancellation or intermediate stopping of the trains etc. This strategy can solve the problem of railway operators than the passenger's problem of missed connecting trains, missed business opportunities or personal appointments etc. To ensure both operator and passenger satisfaction, this paper proposes a novel blockchain‐enabled virtual coupling of automatic train operation fitted mainline trains for railway traffic conflicts. The immutable blockchain databases of the trains and track infrastructures help to forecast the traffic conflicts in real time. Seven variants of virtual coupling strategies are described in this study. Based on the chosen strategy, the reference model of the automatic train operation of mainline trains is virtually coupled or synchronised. Finally, the simulation results and theoretical analyses using several case studies are carried out to confirm the sufficiency of the proposed system and method. The major advantage of the proposed study is that it can be an overlay to the existing European Railway Traffic Management System Level‐2.