基于YOLO的智能交通车辆监控与信号分配

R. P., Sandeep P, Suganyadevi S
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引用次数: 0

摘要

印度的交通控制系统现在对道路上不断增加的车辆数量缺乏灵活性。固定交通灯定时系统是一种很差的控制交通流量的方法。交通灯是交通流控制的基本组成部分,通过预定的等待和行驶时间来控制交通流。根据每条车道上的车辆数量调整交通灯时间的智能方法是智能交通系统的一部分。乘客的平均行程和等待时间将减少,同时交通流的安全性、可靠性和速度都将提高。设计一个有效的自动交通时间节省系统是我们的目标。该系统主要用于交通管理。在这个建议的应用程序中,首先拍摄汽车的照片。首先将图像从RGB转换为灰度,然后使用图像分割方法检索车辆图像。在对准备好的图像进行分割后,神经网络确定单个部分是否包含汽车。成功的部分将被计数器计数。最后,图形用户界面(GUI)将显示每种光色的适当时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Traffic Vehicle monitoring and Signal Allocation using YOLO
The traffic control system in India is now inflexible to the continuously increas-ing number of vehicles on the road. Fixed traffic light timing systems are a poor method of controlling traffic flow. Traffic lights are the fundamental component in traffic flow control through predetermined waiting and going times. A smart approach to adjust traffic light timing based on the number of vehicles in each lane is part of an intelligent traffic system. The average journey and waiting time for passengers will be reduced while the safety, dependability, and speed of the traffic flow is all increased. Designing an effective automated Traffic Time Saving system is the goal. The system is used for traffic management. In this proposed application first takes a picture of the car. Images are first converted from RGB to grayscale, then the vehicle picture is retrieved using image segmentation. After applying segmentation to the ready image, neural networks determine whether or not individual section contains a car. The successful parts will be counted by a counter. Lastly, a Graphical User Interface (GUI) will show the appropriate times for each light color.
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