基于人工智能的红绿灯智能控制

Mihir Gandhi, Devansh S. Solanki, Rutwij S. Daptardar, Nirmala Shinde Baloorkar
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引用次数: 16

摘要

随着城市人口和汽车的增加,交通拥堵已成为城市面临的主要问题之一。交通堵塞不仅给司机造成额外的延误和压力,而且还增加了燃料消耗和空气污染。虽然它似乎无处不在,但大城市是受其影响最大的。道路交通密度的不断增长使得实时计算道路交通密度成为更好的信号控制和有效的交通管理的必要条件。交通控制器是影响交通流的关键因素之一。因此,需要优化交通管制,以更好地适应这一日益增长的需求。我们提出的系统旨在利用交通路口摄像头的实时图像,利用图像处理和人工智能计算交通密度。重点研究了基于车辆密度的红绿灯切换算法,以减少拥堵,从而为人们提供更快的交通,减少污染。
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Smart Control of Traffic Light Using Artificial Intelligence
Traffic congestion is becoming one of the critical issues with increasing population and automobiles in cities. Traffic jams not only cause extra delay and stress for the drivers, but also increase fuel consumption and air pollution. Although it seems to pervade everywhere, megacities are the ones most affected by it. And its ever-increasing nature makes it necessary to calculate the road traffic density in real-time for better signal control and effective traffic management. The traffic controller is one of the critical factors affecting traffic flow. Therefore, the need for optimizing traffic control to better accommodate this increasing demand arises. Our proposed system aims to utilize live images from the cameras at traffic junctions for traffic density calculation using image processing and AI. It also focuses on the algorithm for switching the traffic lights based on the vehicle density to reduce congestion, thereby providing faster transit to people and reducing pollution.
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