Development of Intelligent Traffic Control System by Implementing Fuzzy-logic Controller in Labview and Measuring Vehicle Density by Image Processing Tool in Labview

V. Patel, Maitri N. Patel
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引用次数: 1

Abstract

In this paper, we have described a whole new approach of rationalization of existing traffic control systems by means of Fuzzy logic based control system and Vision sensors based vehicle counting method. As Conventional traffic control systems are inefficient because they provide fixed time-delay though no vehicle is present in that lane. So it results in congestion of vehicles on the adjacent side. And it generates the Noise and Air pollution, which is undesirable and not favorable. In an Intelligent traffic control system (ITCS), vision sensors will measure the number of vehicles on arrival as well as on queue side, and fuzzy logic rule based system will provide the rational time-delay, which is dependent on vehicle density on both arrival and queue side. So it will give zero delays if no vehicle is present in that lane. So ITCS works with intelligence given by the Fuzzy logic system.
在Labview中实现模糊逻辑控制器,在Labview中使用图像处理工具测量车辆密度,开发智能交通控制系统
本文提出了一种基于模糊逻辑的控制系统和基于视觉传感器的车辆计数方法来优化现有交通控制系统的全新方法。由于传统的交通控制系统在没有车辆的情况下提供固定的时间延迟,因此效率低下。这就造成了相邻侧车辆的拥堵。它产生噪音和空气污染,这是不可取的和不利的。在智能交通控制系统(ITCS)中,视觉传感器将测量到达和排队侧的车辆数量,基于模糊逻辑规则的系统将根据到达和排队侧的车辆密度提供合理的延迟。因此,如果车道上没有车辆,它将零延迟。因此,ITCS与模糊逻辑系统赋予的智能一起工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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