Traffic Congestion Analysis Visualisation Tool

N. Petrovska, A. Stevanovic
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引用次数: 34

Abstract

The rapid growth of urban population and numbers of private cars in this modern era, results in increasingly urgent transportation problem in cities throughout the world. Road traffic congestion is an omnipresent problem, which leads to delays, time loss, human stress, energy consumption, environmental pollution e.c.t. In order to decrease traffic congestion, there is a need for simulating and optimizing traffic control and improving traffic management. There are different ways for traffic congestion monitoring and analysis such as using video monitoring and surveillance systems, or static and dynamic sensors which allow traffic management in real time. There are also other methods using non real time analysis where traf?c congestion can be extracted from historical patterns of traf?c congestion. The historical patterns can be gained from the stored travel time and speed data. The goal of enhancing driver convenience is achieved by providing applications based on road traffic condition that mainly identifies congestion status. This paper presents a web application which uses live traffic congestion data from Google Maps traffic layer for real time congestion calculation. A technique utilized for estimating the level of congestion is image processing. The main objective is to provide an automated and yet interactive visualization tool for congestion analysis in real time. The aim is reducing the traffic congestion on roads which will lead to decrease in the number of accidents. It can provide important data which can help road traffic management. Thus, it is mainly dedicated to traffic managers, operators and analysts. Nevertheless it can be implemented also by road users. Unlike most sensor based applications, it makes quantified congestion data available even in regions with limited traffic data information.
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交通拥堵分析可视化工具
在这个时代,城市人口和私家车数量的快速增长,导致世界各地城市的交通问题日益紧迫。道路交通拥堵是一个无处不在的问题,它会导致延误、时间损失、人员压力、能源消耗、环境污染等问题。为了减少交通拥堵,需要模拟和优化交通控制,改进交通管理。交通拥堵的监测和分析有不同的方法,例如使用视频监控系统,或使用静态和动态传感器,以便实时进行交通管理。还有其他方法使用非实时分析哪里的流量?C拥堵可以从历史交通模式中提取出来吗?c拥堵。历史模式可以从存储的旅行时间和速度数据中获得。通过提供主要识别拥堵状态的基于道路交通状况的应用程序来实现提高驾驶员便利性的目标。本文提出了一个利用Google Maps交通层的实时交通拥塞数据进行实时交通拥塞计算的web应用程序。用于估计拥塞程度的一种技术是图像处理。主要目标是为实时拥塞分析提供一个自动化的交互式可视化工具。目的是减少道路上的交通堵塞,从而减少事故的数量。它可以提供有助于道路交通管理的重要数据。因此,它主要面向交通管理人员、运营商和分析师。然而,它也可以由道路使用者实施。与大多数基于传感器的应用程序不同,即使在交通数据信息有限的地区,它也可以获得量化的拥堵数据。
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