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. 2023 Jun 4;23(11):5324.
doi: 10.3390/s23115324.

IoT-Based Emergency Vehicle Services in Intelligent Transportation System

Abdullahi Chowdhury  1 , Shahriar Kaisar  2 , Mahbub E Khoda  3 , Ranesh Naha  4   5 , Mohammad Ali Khoshkholghi  6 , Mahdi Aiash  6
Affiliations

IoT-Based Emergency Vehicle Services in Intelligent Transportation System

Abdullahi Chowdhury et al. Sensors (Basel). .

Abstract

Emergency Management System (EMS) is an important component of Intelligent transportation systems, and its primary objective is to send Emergency Vehicles (EVs) to the location of a reported incident. However, the increasing traffic in urban areas, especially during peak hours, results in the delayed arrival of EVs in many cases, which ultimately leads to higher fatality rates, increased property damage, and higher road congestion. Existing literature addressed this issue by giving higher priority to EVs while traveling to an incident place by changing traffic signals (e.g., making the signals green) on their travel path. A few works have also attempted to find the best route for an EV using traffic information (e.g., number of vehicles, flow rate, and clearance time) at the beginning of the journey. However, these works did not consider congestion or disruption faced by other non-emergency vehicles adjacent to the EV travel path. The selected travel paths are also static and do not consider changing traffic parameters while EVs are en route. To address these issues, this article proposes an Unmanned Aerial Vehicle (UAV) guided priority-based incident management system to assist EVs in obtaining a better clearance time in intersections and thus achieve a lower response time. The proposed model also considers disruption faced by other surrounding non-emergency vehicles adjacent to the EVs' travel path and selects an optimal solution by controlling the traffic signal phase time to ensure that EVs can reach the incident place on time while causing minimal disruption to other on-road vehicles. Simulation results indicate that the proposed model achieves an 8% lower response time for EVs while the clearance time surrounding the incident place is improved by 12%.

Keywords: drone in emergency; emergency vehicle priority; intelligent transportation system.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Drone-assisted incident management system. Here, drones will work as the lead vehicles to guide the EVs to the incident place while alerting other road users.
Figure 2
Figure 2
Workflow of UAV-assisted adaptive route selection strategy.
Figure 3
Figure 3
Cell of road with source and sink.
Figure 4
Figure 4
Density, Flow rate, and Speed changes in different cells during the incident with a 50% occupancy rate. (a) Density at cell 10. (b) Flow rate at Cell 10. (c) Speed change at cell 10.
See this image and copyright information in PMC

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