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首页> 外文期刊>Procedia Computer Science >Decision Support Model for Automated Railway Level Crossing System Using Fuzzy Logic Control
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Decision Support Model for Automated Railway Level Crossing System Using Fuzzy Logic Control

机译：基于模糊逻辑控制的铁路自动道口系统决策支持模型

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This paper aims to discuss a decision support model for automated railway level crossing (LC) using fuzzy logic control (FLC) for providing robust decision making at unmanned railway level crossings, to save the overall operation time, to avoid any accidental fatalities, and to eliminate human errors. The decision support model proposed here provides intelligent decisive action signals as similar to a human brain (e.g. during arrival and departure of trains at railway level crossing). FLC model is designed which recognizes the events (i.e. arrival and departure of trains) and accordingly output action signals are generated (i.e. to warning siren, control actions for opening and closing of gates). This type of model can be implemented in unmanned railway level where the chances of accidents are higher and reliable control operation is required. Three primary inputs to the specified model are considered based on visual, acoustic, and vibration. This novel system makes use of all these three parameters as input for its decision taking parameters, which increases the robustness of this model as compared with previously proposed models where the input is dependent on a single event. The FLC structure implemented to generate this model is multiple input multiple output (MIMO) system.
机译：本文旨在讨论使用模糊逻辑控制（FLC）的自动铁路平交道口（LC）的决策支持模型，以在无人驾驶的铁路平交道口提供可靠的决策，从而节省总体运营时间，避免任何意外伤亡并消除人为错误。这里提出的决策支持模型提供了类似于人脑的智能决定性行动信号（例如，在铁路平交道口的火车到达和离开期间）。设计了FLC模型，该模型识别事件（即火车的到达和离开）并相应地生成输出动作信号（即用于警告警报声，用于打开和关闭车门的控制动作）。这种类型的模型可以在无人驾驶的铁路系统中实现，在这种情况下，发生事故的可能性更高，并且需要可靠的控制操作。根据视觉，听觉和振动，将考虑指定模型的三个主要输入。该新颖的系统将所有这三个参数用作其决策参数的输入，与先前提出的其中输入依赖于单个事件的模型相比，该模型提高了该模型的鲁棒性。为生成此模型而实施的FLC结构是多输入多输出（MIMO）系统。

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