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IoT-Based Emergency Vehicle Services in Intelligent Transportation System.

Abdullahi Chowdhury1, Shahriar Kaisar2, Mahbub E Khoda3

  • 1School of Computer Science, University of Adelaide, Adelaide 5005, Australia.

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Summary
This summary is machine-generated.

This study introduces an Unmanned Aerial Vehicle (UAV) guided system to improve emergency vehicle (EV) response times. By optimizing traffic signals, it reduces EV delays and minimizes disruption to other traffic.

Keywords:
drone in emergencyemergency vehicle priorityintelligent transportation system

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Area of Science:

  • Intelligent Transportation Systems
  • Traffic Engineering
  • Emergency Response Management

Background:

  • Urban traffic congestion delays emergency vehicles (EVs), increasing fatalities and damage.
  • Current methods prioritize EVs by altering traffic signals but neglect non-emergency vehicle disruption and dynamic traffic changes.
  • Existing routing strategies for EVs are static and fail to adapt to real-time traffic conditions.

Purpose of the Study:

  • To propose an Unmanned Aerial Vehicle (UAV) guided, priority-based incident management system.
  • To reduce emergency vehicle (EV) response times by improving intersection clearance.
  • To minimize disruption to non-emergency vehicles during EV transit.

Main Methods:

  • Development of a novel Unmanned Aerial Vehicle (UAV) guided incident management system.
  • Implementation of a priority-based algorithm considering both EV and non-emergency vehicle traffic.
  • Dynamic traffic signal phase control to optimize traffic flow and clearance times.

Main Results:

  • Achieved an 8% reduction in emergency vehicle (EV) response times.
  • Improved traffic clearance time around incident locations by 12%.
  • Demonstrated a balanced approach to prioritizing EVs while mitigating disruption to other road users.

Conclusions:

  • The proposed UAV-guided system effectively reduces emergency response times.
  • The system successfully balances the needs of emergency vehicles with the flow of regular traffic.
  • This approach offers a significant advancement in intelligent transportation systems for incident management.