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Satellite-based localization solutions are expected to boost railway digitalization and in particular, they will enhance evolution and efficiency of railway signaling systems. The development of multi-sensor solutions is ongoing, but some gaps remain. This paper addresses two of them: the need for innovative high accuracy and precision Ground Truth and Digital Maps, essential elements of a EGNSS train positioning system and a V&V environment. These two objectives are focused in the RAILGAP EU project. For each of these tools, this paper presents the main high-level requirements and the selected architectural design exploiting specific data fusion algorithms. The novelty of the EGNSS multi-sensor solution proposed is that it does not require to install or modify any equipment on the track. It is based on datasets acquired through commercial runs in Italy and Spain, leveraging on regular train trips in different operational scenarios and time.

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Railway Ground Truth and Digital Map Based on GNSS and Multi-sensor Big-Data Acquisition

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Alessandro Neri,
  • Alessia Vennarini,
  • Agostino Ruggeri,
  • Juliette Marais,
  • Nourdine Aït Tmazirte,
  • Omar Garcia Crespillo,
  • Anja Grosch,
  • María-Eva Ramírez,
  • Juan-Gabriel Arroyo,
  • Massimiliano Ciaffi,
  • Giusy Emmanuele,
  • Vittorio Cataffo,
  • Ricardo Campo Cascallana,
  • Daniel Molina Marinas,
  • Alessandro Valentini,
  • Stefano Neri,
  • Fabrizio Memmi,
  • Ramiro Valdés Alvarez-Palencia,
  • Gianluigi Lauro,
  • Pasquale Natale

摘要

Satellite-based localization solutions are expected to boost railway digitalization and in particular, they will enhance evolution and efficiency of railway signaling systems. The development of multi-sensor solutions is ongoing, but some gaps remain. This paper addresses two of them: the need for innovative high accuracy and precision Ground Truth and Digital Maps, essential elements of a EGNSS train positioning system and a V&V environment. These two objectives are focused in the RAILGAP EU project. For each of these tools, this paper presents the main high-level requirements and the selected architectural design exploiting specific data fusion algorithms. The novelty of the EGNSS multi-sensor solution proposed is that it does not require to install or modify any equipment on the track. It is based on datasets acquired through commercial runs in Italy and Spain, leveraging on regular train trips in different operational scenarios and time.