Overview

The RAILGAP project is an essential step towards to fostering green, safe and smart mobility. The prospect is to further enhance the recognised “green” characteristic of the rail transport consuming less than 2% of electricity in Europe and generating 1/10 of CO2 emission per passenger with respect to airplanes. The adoption of EGNSS for train positioning and for supporting key phases of the CENELEC system life cycle (e.g. design and development phases, V&V phases, maintenance phase) is crucial to cut the life-cycle cost of railway transports, increase the railway capacity, reliability and punctuality and minimise the consumption of energy per passengers km.

RAILGAP intends to contribute to the roadmap towards the adoption of EGNSS for not-safe and safe applications (e.g. satellite positioning in the railways ERTMS ecosystem). Considering the past and ongoing initiatives, we identified the need of new methodologies and tools, i.e. a Ground Truth and a Digital Map which are not available today with the required quality and performance attributes, for the evaluation and assessment of new on-board signalling systems or their enhancements (by using and processing data resulted from hybridization of sensors (GNSS, IMU, LIDAR, cameras, odometers…). State of the art technologies will be used and will optimise both the trackside signalling design where a Digital Map is required and the verification activities of on-board equipment where the knowledge of true positions, accelerations, and speeds is mandatory (i. e. knowledge of the Ground Truth).

Indeed, a Ground Truth becomes essential to characterize, evaluate and assess any solutions with impact on the train position or train dynamics that are explored or still ongoing. On the other hand, the availability of a Digital Map also becomes mandatory in order to make use of ATO algorithms and new Train Position algorithms. Both are missing due to the lack of adequate and low cost tools. This is why RAILGAP will focus on the novel methodologies and toolset for building a high precision and accuracy ground truth and a digital trackside map with integrity requirements.

RAILGAP is the first project that will use Commercial trains to collect massive data from the fields, overcoming the limitations arising from limited test campaigns performed so far and the lack of meaning performance of non-EGNSS sensors in the rail ecosystem.




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