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Advanced Traffic Management And Control Systems

IP Coordinator:Antonella Trombetta - HITACHI RAIL STS

Overview

Project title:

Topic:
H2020-S2RJU-OC-2017
Total Project Value:
€ 1 797 307,50
Duration:
from 01/09/2017 to 31/10/2019
S2R (Of H2020) co-funding:
€ 1 797 307,50
Coordinator:
Riccardo Scopigno
ISTITUTO SUPERIORE MARIO BOELLA SULLE TECNOLOGIE DELL'INFORMAZIONE E DELLE TELECOMUNICAZIONI ASSOCIA
Complementary projects:
Project website:

Objective

The main objective of ASTRail is to increase the efficiency and safety in the railway sector. ASTRail will contribute to enhancing the signalling and automation of the railway system thanks to innovative solutions that exploit cutting edge technologies already in use in sectors different from the rail, such as the aeronautic or the automotive sectors. Investigation of such technologies and assessment of their reusability in the railway field will be done taking particular care of issues related to safety and performance in the rail system.

ASTRail will in particular, address the following specific objectives:

  • leveraging the expertise of the aeronautic sector on GNSS technology to improve localization of trains; ASTRail will define which assumptions and requirements about GNSS technology can be transferred from the aeronautical standards to the railway system; ASTRail will define architecture, specific algorithms, and the software definition for testing purposes in order to assess the minimum achievable performance by GNSS technology in the railway system; the overall result will be an informed setting of “Minimum Performance Requirements for GNSS technology in the ERTMS Signalling System”;
  • defining a model of the Moving Block Signalling system and perform its Hazard Analysis considering use cases that will be defined by parameters such a system state (degraded operation, transition phases), traffic type, environmental condition (tunnels, urban areas, etc.) and Grade of Automation;
  • identifying which automatic driving technologies can be reused in the railway sector from the automotive or other application fields, such as maritime and aeronautics sectors, or even agriculture; ASTRail will further contribute to the development of Automatic Train Operation by analysing which characteristics and requirements of the identified technologies can be also applicable to the railway field and it will assess the most suitable technologies that can be reused in the railway; all results achieved will be contained in the report “Recommendations on Automatic Driving in the Railway Sector”;
  • reviewing and assess the main formal modelling and verification languages and tools used in industrial railway applications, as well as the most promising ones highlighted by the scientific literature; ASTRail will take further the analysis to define the optimal set of languages and tools and will validate them with representative components deriving from other tasks of the project.


Results and Publications

D1.1 Aeronautical Standards Review

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D1.2 Local GNSS Effects

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D1.3 The ERTMS hazards associated with GNSS faults

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D1.4 GNSS algorithms design

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D1.5 GNSS Solutions Report

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D1.6 Proposed GNSS Minimum Performance Requirements

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D2.1 Modelling of the moving block signalling system

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D2.2 Moving Block signalling system Hazard Analysis

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D3.1 State of the Art of Automated Driving technologies

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D3.2 Automatic Train Operations implementation operation characteristics and technologies for the Ra

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D4.1 Report on Preliminary Analysis and on Rankingof Formal Methods

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D4.2 Preliminary Trial Report

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D4.3 Validation Report

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D5.1 Set up public website

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D5.2 Set up a dissemination and exploitation plan for the project

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D5.3 Dissemination and Exploitation activities

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D5.4 Report on the project results_achievements for future S2R activities

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All deliverables, results and publications herewith provided reflects only the author's view and the S2R JU is not responsible for any use that may be made of the information it contains.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No: 777561