基于GPS的智能交通监控、排序与控制模型

Monica C, B. Jyothi, Amogh Ramagiri, Sathwik Gottipati, V. Jahnavi, Syed Afreen Akther, R. Chinnaiyan
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引用次数: 0

摘要

随着全球人口的增长和新兴技术的发展,人们迫切需要高效的交通管理系统。遗憾的是,传统的交通控制系统依赖于三色信号,无法对紧急车辆进行优先排序,也无法有效地控制交通。造成事故、生命损失和交通堵塞。但是,提供实时交通数据和紧急车辆跟踪的全球定位系统(GPS)、预测交通解决方案的人工智能(AI)和深度学习(DL)、处理数据的云计算、收集实时数据并提供有前景的解决方案的物联网(IoI)等最新技术。其中一些挑战包括各种技术的集成、算法的复杂性、可扩展性问题、安全性和隐私性。本文研究了人工智能、物联网和GPS在交通管理中的作用,提出了一种更好的交通信号管理系统,可以减少拥堵,优先安排应急车辆,减少通勤时间并跟踪车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Traffic Monitoring, Prioritizing and Controlling Model based on GPS
With the increasing global population and emerging technologies, there is a pressing need for efficient traffic management systems. Unfortunately, the traditional traffic control system, which relies on tri-colour signals is unable to prioritize emergency vehicles or control traffic effectively. Resulting in accidents, loss of life, and traffic congestion. However, recent technologies such as GPS, which provides live traffic data and emergency vehicle tracking, Artificial Intelligence (AI) and Deep Learning (DL), which can predict traffic solutions, Cloud Computing it processes the data and Internet of Things (IoI), which collects real-time data and offers promising solutions. Some of the challenges include the integration of various technologies, complexity in algorithms, scalability concerns, security and privacy. In this paper, we present a study on the role of AI, IoT and GPS in traffic management, proposing a better traffic signal management system that reduces congestion, prioritizes emergency vehicles, reduces commuting time and tracks vehicles.
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