Optimization of Smart Traffic Governance System Using Artificial Intelligence

Aayush Sukhadia, Khush Upadhyay, Meghashree Gundeti, Smit Shah, Manan Shah
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引用次数: 37

Abstract

Traffic system shows a great scope of trade with the environment and is directly connected to it. Manual traffic systems are proving to be insufficient due to rapid urbanization. Central monitoring systems are facing scalability issues as they process increasing amounts of data received from hundreds of traffic cameras. Major traffic problems include congestion, safety, pollution (leading to various health issues) and increased need for mobility. A solution to most of them is the construction of newer and safer highways and additional lanes on existing ones, but it proves to be expensive and often not feasible. Cities are limited by space, and construction cannot keep up with ever-growing demand. Hence, a need for an improved system with a minimal manual interface is persisting. One of such methods is introduced and discussed in this paper; smart traffic governance system here used artificial intelligence to regulate and govern the course of transport and automated administration and implementation to make a difference in face of travel scenarios in urban cities suffering from such major traffic issues.

Abstract Image

基于人工智能的智能交通治理系统优化
交通系统显示出与环境的巨大贸易范围,并与环境直接相关。由于快速的城市化,人工交通系统被证明是不够的。中央监控系统在处理从数百个交通摄像头接收到的越来越多的数据时,面临着可扩展性问题。主要的交通问题包括拥堵、安全、污染(导致各种健康问题)和对出行需求的增加。其中大多数的解决方案是在现有公路上建造更新、更安全的公路和额外的车道,但事实证明,这是昂贵的,而且往往不可行。城市受到空间的限制,建筑无法跟上日益增长的需求。因此,对具有最小手动接口的改进系统的需求一直存在。本文介绍并讨论了其中一种方法;这里的智能交通治理系统利用人工智能来规范和治理交通过程,并通过自动化管理和实施来改变城市中面临此类重大交通问题的出行场景。
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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