铁路安全机动嵌入式控制装置的算法

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
A. Beinarovica, M. Gorobetz, Ivars Alps
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引用次数: 0

摘要

摘要:本文研究了在无编组驼峰的车站工作时的机动决策问题。这是旨在开发自动驾驶电动汽车和一般交通工具的智能安全和最佳控制系统的项目的一部分。主要演习的安全性取决于轨道上物品和其他物体的缺乏以及出入口的位置。在大多数情况下,被其他货车占用的轨道以及错误的出岔口位置都标有禁止通行的红色或蓝色信号灯。提出了一种将卷积神经网络(CNN)与交通信号灯识别相结合的红绿灯识别算法。但是,也会出现机车需要在被其他车厢占用的轨道上行驶的情况,例如在火车站进行机动时。为此,作者开发了一种用于轨道上车辆识别的CNN算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms for Railway Embedded Control Devices for Safety Manoeuvres
Abstract This study is dedicated to solve manoeuvres making task while working on the station with no marshalling hump. It is part of the project aimed at the development of intelligent safety and optimal control systems of autonomous electric vehicles and transport in general. The main manoeuvres safety depends on the lack of items and other objects on the rails as well as on the position of turnouts. In most cases rails, occupied with other wagons, as well as the wrong position of turnouts are marked with prohibiting red or blue signals of the traffic light. The authors propose an algorithm for the traffic light recognition by using a convolutional neural network (CNN) and traffic light indicator recognition. However, the situation when the locomotive needs to drive on the rails occupied with other wagons, for example, during the manoeuvres on the railway station can also appear. For this purpose, the authors have developed a CNN algorithm for the wagon recognition on the rails.
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来源期刊
Electrical Control and Communication Engineering
Electrical Control and Communication Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
自引率
14.30%
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0
审稿时长
12 weeks
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