This paper introduces a framework to ensure the semantic integrity of Control-Command and Signaling (CCS) design data, essential for reliable and efficient planning processes. Traditional XML Schema checks address syntax but fail to capture the complex logic required for CCS systems. To overcome this, we apply the Schematron standard to formally validate complex railway signaling rules. Our approach is to translate natural language constraints into semi-formal semantic rules that are implemented and tested. We extend Schematron with technology- and domain-specific features, such as data indexing and advanced error reporting. These innovations enable scalability for large datasets while producing clear, actionable reports for signaling engineers, safety assessors, and infrastructure managers. Applied to DB InfraGO’s PlanPro data format, our framework automates processes that improve data quality, reduce human error, and accelerate CCS planning. By supporting formal workflows, it strengthens safety assurance and regulatory compliance, addressing key challenges in the railway domain. Its integration into the “Werkzeugkoffer” toolkit demonstrates its practical value in tackling the complexities of modern railway control systems.

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Automated Semantic Validation of Railway Signaling Data on the Basis of Schematron

  • Susanne Wunsch,
  • Birgit Jaekel,
  • Martin Lehnert,
  • Christoph Klaus,
  • Jan Gruteser,
  • Michael Leuschel

摘要

This paper introduces a framework to ensure the semantic integrity of Control-Command and Signaling (CCS) design data, essential for reliable and efficient planning processes. Traditional XML Schema checks address syntax but fail to capture the complex logic required for CCS systems. To overcome this, we apply the Schematron standard to formally validate complex railway signaling rules. Our approach is to translate natural language constraints into semi-formal semantic rules that are implemented and tested. We extend Schematron with technology- and domain-specific features, such as data indexing and advanced error reporting. These innovations enable scalability for large datasets while producing clear, actionable reports for signaling engineers, safety assessors, and infrastructure managers. Applied to DB InfraGO’s PlanPro data format, our framework automates processes that improve data quality, reduce human error, and accelerate CCS planning. By supporting formal workflows, it strengthens safety assurance and regulatory compliance, addressing key challenges in the railway domain. Its integration into the “Werkzeugkoffer” toolkit demonstrates its practical value in tackling the complexities of modern railway control systems.