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04.01.2022 | Special Issue Article

Ultra-safe and reliable enhanced train-centric communication-based train control system

verfasst von: Djamila Zamouche, Mohamed Mohammedi, Sofiane Aissani, Mawloud Omar

Erschienen in: Computing | Ausgabe 3/2022

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Abstract

The autonomous vehicles emergence is a significant step forward in the development of safe and dependable intelligent transportation systems. In vehicular automation, digital connectivity has been one of the most critical specifications. In this paper, we focus on the autonomous train, which is one of the most rapidly growing applications of autonomous vehicles. In this context, we address the issue of safety by the proposition of Enhanced Train-centric Communication-Based Train Control (ETcCBTC), which provides efficient control of rail traffic. To ensure the operation’s safety, we’ve implemented a new safety-checking approach based on process algebra, which aims to track and correct in real time the train behavior. The proposed ETcCBTC system’s performance is tested using extensive simulations and compared to CBTC and TcCBTC. In terms of checking success, transmission load, and response time, the obtained results demonstrate that ETcCBTC outperforms the concurrent systems.

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The generated safety policy that the train must respect during its movement is the only variation.

This formalism is similar to Markov model as they are both state transition models. The Markovian formalism gives the probability of the system be in a specific state at a given time. However, our framework operates with a continuous monitoring, this is allowed thanks to the continuous calculation of the greater common behavior \(P\sqcap Q\). In the other hand, unlike the Markovian models, our system does not just alert, but it offers the correct behavior that the train should follow.

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Titel: Ultra-safe and reliable enhanced train-centric communication-based train control system
verfasst von: Djamila Zamouche
Mohamed Mohammedi
Sofiane Aissani
Mawloud Omar
Publikationsdatum: 04.01.2022
Verlag: Springer Vienna
Erschienen in: Computing / Ausgabe 3/2022
Print ISSN: 0010-485X
Elektronische ISSN: 1436-5057
DOI: https://doi.org/10.1007/s00607-021-01009-6

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