A review of computational intelligence methods for traffic management systems

Put i Saobracaj Pub Date : 2021-12-17 DOI:10.31075/67.04.05
V. Ilin, D. Simić
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引用次数: 1

Abstract

One of the most important challenges in modern city life is to enable effective and efficient traffic management system. Recently, computational intelligence methods have become increasingly popular for traffic management system design, application, and monitoring. Computational intelligence methods are often deployed for managing traffic, that is for reducing mileage, congestion, the use of fuels, and environmental impact. The aim of this paper is twofold. First, to present the three main areas in a computational intelligence approach, namely neural networks, fuzzy logic systems, and evolutionary computation. Second, to emphasize their impact on various traffic management domains, including traffic flow forecasting, traffic light control, traffic fatalities prediction, traffic sign detection, and optimization of transportation networks.
交通管理系统的计算智能方法综述
现代城市生活中最重要的挑战之一是实现有效和高效的交通管理系统。近年来,计算智能方法在交通管理系统的设计、应用和监控中越来越受欢迎。计算智能方法通常用于管理交通,即减少里程、拥堵、燃料使用和环境影响。本文的目的是双重的。首先,介绍计算智能方法的三个主要领域,即神经网络、模糊逻辑系统和进化计算。其次,强调其在交通流量预测、交通信号灯控制、交通死亡人数预测、交通标志检测和交通网络优化等各个交通管理领域的影响。
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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来源期刊
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发文量
34
审稿时长
6 weeks
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