Railway Ground truth and digital map
Background & Objectives
RAILGAP 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 EUSPA 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.