IoT-Based Emergency Vehicle Services in Intelligent Transportation System

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.