Descripción del proyecto
Datos de gran calidad que guían a unos trenes innovadores
La innovación en el sector ferroviario afronta dos retos fundamentales, a saber: la falta de observaciones de gran calidad con datos validados sobre el terreno, que son esenciales para desarrollar nuevos sistemas de navegación, y un proceso de modernizado de cartografiado de las vías ferroviarias actuales de bajo coste y que obtiene información cartográfica directamente de los trenes en funcionamiento. Abordar estos retos requiere en la práctica una metodología para recopilar y reunir datos a un coste mínimo. El objetivo del proyecto financiado con fondos europeos RAILGAP es conseguir trenes ecológicos, sostenibles, seguros y con movilidad inteligente. Para ello, se desarrollarán mapas digitales y temáticos con datos validados sobre el terreno avanzados y de alta precisión, elementos esenciales de un sistema de posicionamiento de trenes basado en el sistema mundial de navegación por satélite europeo y un entorno de verificación y validación. RAILGAP recopilará además cantidades ingentes de datos de trenes comerciales.
Objetivo
RAILGARAILGAP is an essential step towards green, safe, smart mobility on rails. It focuses on developing innovative High Accuracy, High Precision Ground Truth and Digital Maps, essential elements of an EGNSS train positioning system and a V&V Environment. The outcomes will address two show stoppers: lack of high-quality data with ground truth (needed for developing new navigation systems) and a modernized process for mapping existing train tracks cost-effectively, by deriving mapping information directly from trains in commercial operation. This will enable positioning with unprecedented reliability and efficiency in the railway operations. The missing piece is a methodology to collect and aggregate the data without operational overheads or labour, at minimal cost in hardware while removing any need for trackside infrastructure. RAILGAP addresses these challenges with a method based on commercial trains collecting massive amounts of data. This enables characterizing even the most challenging railway environments. Results will support the GSA roadmap in adopting EGNSS in train Command & Control Systems (CCS) and trigger contributions from stakeholders. We will exploit a fusion of GNSS with data from other sensors as IMU, Lidar and Camera. Dual-Freq., Multi-Const. GNSS is key to improving map accuracy in challenging environments (urban areas, tree canopies) extending coverage of GNSS on rails. RAILGAP will make ERTMS and CCS with EGNSS sustainable, helping modernise regional and local lines, where passengers will benefit daily. It also enhances the case for ERTMS and CCS by lowering energy consumption. Project coordinator is RFI, who has been very involved in piloting GNSS-based technology for ERTMS like the Novara-Rho pilot line. The team has experts in rail and satellite navigation and includes research organizations, engineering consultants, railway operators and stakeholder representatives, forming a well-recognized consortium with long-term working experience.
Ámbito científico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- social sciencessocial geographytransportnavigation systemssatellite navigation systemglobal navigation satellite system
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SPACE-EGNSS-2020
Régimen de financiación
IA - Innovation actionCoordinador
00161 Roma
Italia