As a part of the digital revolution of railway systems, an autonomous driving train will use a complete and precise map of railway infrastructure to conduct operational actions. Nevertheless, the full autonomy of trains depends on the safety decisions management capacity both on-board and track-side. These decisions must be refined into safety requirements in order to continuously check the consistency between the perceived infrastructure and safety related properties. However, traditionally, the integration of safety analysis requires the intervention of human agent skills. This may be error-prone and in interference with the embedded aspect of the train map. In this paper, we propose a model-based approach to match between safety concepts expressed as an ontology, a derived safety model and a safety-extended railway infrastructure map model for autonomous trains. This approach is validated by railway safety case studies for autonomous train map. The integration of this model-based safety solution from the early stages of the map system design improves the safety decisions management process.

作为铁路系统数字化革命的一部分，自动驾驶列车将使用完整、精确的铁路基础设施地图进行运营行动。然而，列车的完全自主性取决于车载和轨道侧的安全决策管理能力。这些决策必须细化为安全要求，以便持续检查感知基础设施与安全相关属性之间的一致性。但是，传统上，安全分析的集成需要人工代理技能的干预。这可能容易出错并且会干扰火车地图的嵌入方面。在本文中，我们提出了一种基于模型的方法来匹配表示为本体的安全概念，自动列车的派生安全模型和安全扩展铁路基础设施地图模型。这种方法已通过自动列车地图的铁路安全案例研究得到验证。从地图系统设计的早期阶段就集成了这种基于模型的安全解决方案，从而改进了安全决策管理流程。