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Related Experiment Video

Updated: Mar 26, 2026

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A Survey on Urban Traffic Management System Using Wireless Sensor Networks.

Kapileswar Nellore1, Gerhard P Hancke2

  • 1Advanced Sensor Networks Research Group, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa. u15342396@tuks.co.za.

Sensors (Basel, Switzerland)
|February 2, 2016
PubMed
Summary

Wireless Sensor Networks (WSNs) offer efficient traffic detection and management solutions. This survey explores WSN-based systems for reducing road congestion and prioritizing emergency vehicles, improving urban mobility.

Keywords:
Average Waiting Time (AWT)Wireless Sensor Networks (WSNs)emergency vehicle priorityintelligent traffic light controllerstraffic congestiontraffic parameterstraffic sensing systems

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Area of Science:

  • * Transportation Engineering
  • * Computer Networks
  • * Urban Planning

Background:

  • * Exponential vehicle growth overwhelms static road infrastructure, leading to traffic congestion and pollution.
  • * Traditional traffic control systems fail to manage traffic effectively and can impede emergency vehicle access.
  • * Wireless Sensor Networks (WSNs) offer a promising, cost-effective solution for real-time traffic monitoring and management.

Purpose of the Study:

  • * To survey and categorize current urban traffic management schemes focused on congestion avoidance.
  • * To analyze systems that utilize Wireless Sensor Networks (WSNs) for intelligent traffic control.
  • * To provide a foundation for future research in optimizing urban traffic flow and emergency vehicle prioritization.

Main Methods:

  • * Comprehensive literature review of existing urban traffic management schemes.
  • * Analysis of systems employing Wireless Sensor Networks (WSNs), RFIDs, ZigBee, VANETs, and other technologies.
  • * Taxonomy development for different congestion avoidance strategies.

Main Results:

  • * WSNs are identified as a key technology for real-time traffic monitoring and adaptive signal control.
  • * Various WSN-based approaches effectively reduce traffic congestion and average waiting times (AWT).
  • * Systems prioritizing emergency vehicles demonstrate significant improvements in response times.

Conclusions:

  • * WSNs provide a flexible, efficient, and cost-effective solution for modern urban traffic management.
  • * Implementing priority-based signaling and congestion reduction strategies enhances overall traffic efficiency.
  • * Further research into WSN integration can optimize traffic flow and emergency response in urban environments.