The objective of the RADIUS proposal is to develop a drone – based technology to: (1) Monitor the physical status and electronic functionality of both non safety – critical and safety - critical railway signalling assets (2) Execute specific maintenance activities. RADIUS will focus on: (1) The identification of the best drone technology to be used in the railway sector, considering mainly the signalling assets to be monitored, the characteristics of the lines, the maintenance actions to be implemented and the distances to be covered (2) The design a/o the utilization of drone solution and related payloads capabilities to integrate: a. Sensors, data collection and processing capabilities to allow the monitoring of signalling assets b. Wireless technology to be used to provide a secure communication channel between the drone and the peripheral device, and to allow contactless diagnostic and SW maintenance c. Use of EGNSS solutions for navigation and positioning, such as GALILEO and EGNOS (SBAS), enabling improved drone flight control and safe movements in the complex railways operational scenario d. The most secure data transmission solution to guarantee reliable and secure data exchanges, and embedded data analytics to perform assets monitoring, maintenance prediction analysis, and repairing actions avoiding railway track possession (3) The adaptation a/o redesign of the railway signalling assets to become drone – friendly for the maintenance activities, including the design of a docking station (4) The interaction with existing Intelligent Asset Management Systems (5) The interaction with current Traffic Management Systems, to improve the safe movements of drones within the railway (6) The planning of drone mission strategies in compliance with applicable regulations and with the complexity of the railway environment to fly Beyond Visual Line Of Sight (7) The practical demonstration of a proof of concept (TRL 6) system in a railway relevant environment.

The main objective of the FCH2RAIL project is to develop, build, test, demonstrate and homologate a scalable, modular and multi-purpose Fuel Cell Hybrid PowerPack (FCHPP) applicable for different rail applications (multiple unit, mainline and shunting locomotives) also suitable to for retrofit existing electric and diesel trains, to reach TRL7. The project will start with a multi-country, multi railway-use-case analysis in order to derive requirements for the design, implementation and test of the FCHPP. Based on that the FCHPP will be designed and demonstrated in a retrofitted Bi-mode multiple unit that draws electricity from the catenary while operating on electrified sections and uses the FCH system as power source on non-electrified sections supported by an innovative train wide energy management system to minimise the energy and power consumption. In order to improve the energy efficiency of FCH traction systems, innovative on-board solutions are identified and benchmarked. The train demonstrator tests will be carried out cross-border in Portugal and Spain and homologation will be seeked for three EU countries. A systematic screening of H2 and rail related EU-wide normative and standard frameworks concerning gaps related to an EU-wide implementation of FCH Bi-mode trains will be carried out. These activities, closely interconnected to the design, testing and homologation of the FCHPP demonstrator train activities, will result in the proposition of changes to and active involvement in standardization and norming workgroups. An important aim of the FCH2RAIL project is to demonstrate the competitiveness of FCH against diesel trains. Therefore, project related KPI are collected and implemented to a LCC model which is applied to different rail sectors deriving cost reduction potentials. Dissemination will comprise the demonstration of the FCHPP and the train demonstrator complemented by intensive communication and publication activities.

INFRALERT aims to develop an expert-based information system to support and automate linear asset infrastructure management from measurement to maintenance. This enfolds the collection, storage and analysis of inspection data, the deduction of interventions to keep the performance of the network in optimal condition, and the optimal planning of maintenance interventions. It will also assess new construction strategic decisions. The condition of the land transport infrastructure has a big societal and economic relevance, since constraints result in disruptions of service. The demand for surface transport will significantly increase in the next years. Given budget restrictions, a substantial enlargement of the road/rail network in the next decades is doubtful. Besides, the aging infrastructure will require more maintenance interventions which infer normal traffic operation. Therefore, the only way to increase infrastructure capacity for the increased transportation demand is to optimise the performance of the existing infrastructure. This issue is addressed by INFRALERT. INFRALERT will develop and deploy solutions that enhance the infrastructure performance and adapt its capacity to growing needs by: (i) ensuring the operability under traffic disruptions; (ii) keeping and increasing the availability by optimising operational maintenance interventions and assessing strategic long-term decisions on new construction; and (iii) ensuring service reliability and safety by minimising incidences and failures. INFRALERT will be directly applicable by Rail and Road Infrastructure Managers in the field of Intelligent Maintenance and long term strategic planning. Two real pilots (for roads and rail transport systems) will be used to validate and demonstrate the results of the research activities. In both cases, extensive data from auscultation campaigns are available since some years ago. The empirical development of the whole project will be based on these pilot cases.