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As the French railway infrastructure manager, SNCF Réseau is in charge of the maintenance and periodic renewal of the national rail network. To achieve the latter goal with due regard to economic and technical performance as well as the security of daily freight and passenger trains, industrial methods can be used that consist of high-output track and catenary renewal trains (factory trains, known as “suites rapides" in French). To be efficiently used, these expensive machines require planning that takes local weather conditions into account. To this end, a Decision Support Tool called MetProgRé (Météo Programmation Régénération) has been developed in order to assess and minimize disruption due to extreme weather conditions affecting track, catenary or working conditions for the operatives involved. This paper presents MetProgRé giving details regarding the statistical data used and the model implementation. It also provides some insight into use cases and lessons learned during works between 2021 and 2023 when compared to previsions from the model.

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MetProgRé: a Decision Support System to assess Weather Risk for Planning of Railway Renewal Works

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Camille Morvant,
  • Emmanuel Cieren,
  • Sirine Kahil,
  • Sami El Idrissi Raghni,
  • Rawya Zreik,
  • Maxime Gueguin

摘要

As the French railway infrastructure manager, SNCF Réseau is in charge of the maintenance and periodic renewal of the national rail network. To achieve the latter goal with due regard to economic and technical performance as well as the security of daily freight and passenger trains, industrial methods can be used that consist of high-output track and catenary renewal trains (factory trains, known as “suites rapides" in French). To be efficiently used, these expensive machines require planning that takes local weather conditions into account. To this end, a Decision Support Tool called MetProgRé (Météo Programmation Régénération) has been developed in order to assess and minimize disruption due to extreme weather conditions affecting track, catenary or working conditions for the operatives involved. This paper presents MetProgRé giving details regarding the statistical data used and the model implementation. It also provides some insight into use cases and lessons learned during works between 2021 and 2023 when compared to previsions from the model.