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Predictive simulation models are one of the cornerstones of an interactive Local Digital Twin (LDT) for evidence-based policy-making. To ensure the reliability of digital twin data for decisions, it’s important to understand how data is accessed and used by the simulation models. Mapping how models interoperate and can influence each other, what frameworks are needed for standardised event exchanges, and what types of design principles and implementation rules should be followed is crucial. The goal should be a trusted, interoperable ecosystem between open and proprietary models.

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Future Ready Local Digital Twins and the Use of Predictive Simulations: The Case of Traffic and Traffic Impact Modelling

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Chris Tampère,
  • Paul Ortmann,
  • Karel Jedlička,
  • Walter Lohman,
  • Stijn Janssen

摘要

Predictive simulation models are one of the cornerstones of an interactive Local Digital Twin (LDT) for evidence-based policy-making. To ensure the reliability of digital twin data for decisions, it’s important to understand how data is accessed and used by the simulation models. Mapping how models interoperate and can influence each other, what frameworks are needed for standardised event exchanges, and what types of design principles and implementation rules should be followed is crucial. The goal should be a trusted, interoperable ecosystem between open and proprietary models.