Applying Virtual Modelling to Verify Control Systems Decision with Artificial Intelligence in Railway Transport

R. Gorbachev, A. Novikov, A. Kalinkin, Artem Cheranev, E. Zakharova
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Abstract

This paper describes the applying of simulation modelling as a method for verifying the decision support system and forecasting railway traffic in the dispatching management of railway transport. This decision support system would be realised using artificial intelligence methods and on the training, stage requires an additional check of those decisions. For this purpose, a railway traffic model on a test railway section was implemented using a virtual model of the railway section's infrastructure. A virtual model of the railway section infrastructure is realised using the MPC-EL microprocessor-based centralization of arrows and traffic lights. The combination of a virtual railway section and a railway traffic model form a unified system. This system making a forecast train schedule based on initial data of solutions which are received from the decision support system. The verification of solutions obtained from the DSS would check this railway schedule practicability in real conditions. An additional feature of that system supporting the ability to work on workstations with the Elbrus processor, which in turn contributes substitution to the imported component base on the Russian Railways.
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应用虚拟建模技术验证铁路运输控制系统的人工智能决策
本文介绍了仿真建模作为一种验证决策支持系统和预测铁路交通的方法在铁路运输调度管理中的应用。这个决策支持系统将使用人工智能方法实现,在训练阶段需要对这些决策进行额外的检查。为此,使用铁路路段基础设施的虚拟模型实现了测试铁路路段的铁路交通模型。利用基于MPC-EL微处理器的箭头和交通灯的集中化实现了铁路路段基础设施的虚拟模型。虚拟铁路断面与轨道交通模型相结合,形成一个统一的系统。该系统根据从决策支持系统接收到的方案初始数据进行列车时刻表预测。通过对DSS求解结果的验证,验证了该列车时刻表在实际工况下的实用性。该系统的另一个特性支持在带有Elbrus处理器的工作站上工作的能力,这反过来又有助于替代基于俄罗斯铁路的进口组件。
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