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Visualization Tools for Traffic Congestion Estimation

  • Natasha Petrovska
  • Aleksandar Stevanovic
  • Borko Furht
Chapter
  • 346 Downloads
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

The rapid growth of urban population and number 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 etc. 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 traffic congestion can be extracted from historical patterns of traffic 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 section 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. The application 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.

Keywords

Road Segment Traffic Congestion Congestion Level Road Link Interactive Visualization Tool 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© The Author(s) 2016

Authors and Affiliations

  • Natasha Petrovska
    • 1
  • Aleksandar Stevanovic
    • 1
  • Borko Furht
    • 1
  1. 1.Florida Atlantic UniversityBoca RatonUSA

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