- Title
- IoT-based emergency vehicle services in intelligent transportation system
- Creator
- Chowdhury, Abdullahi; Kaisar, Shahriar; Khoda, Mahbub; Naha, Ranesh; Khoshkholghi, Mohammad; Aiash, Mahdi
- Date
- 2023
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/194278
- Identifier
- vital:18318
- Identifier
-
https://doi.org/10.3390/s23115324
- Identifier
- ISSN:1424-8220
- 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%.
- Publisher
- MDPI AG
- Relation
- Sensors Vol. 23, no. 11 (2023), p. 5324
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright authors
- Rights
- Open Access
- Subject
- Ambulances; Analysis; Automobile safety; Clearances; Computer Simulation; Controllers; Disruption; Drone aircraft; drone in emergency; Drones; Electric vehicles; Emergency management; Emergency Medical Services; emergency vehicle priority; Emergency vehicles; Fatalities; intelligent transportation system; Intelligent transportation systems; Peak hour traffic; Pedestrians; Preemption; Property damage; Response time; Roads & highways; Sensors; Simulation; Traffic accidents & safety; Traffic congestion; Traffic control; Traffic flow; Traffic information; Traffic signals; Transportation; Transportation equipment industry; Transportation industry; Travel; Unmanned aerial vehicles; Urban areas; Vehicles; 4008 Electrical engineering; 4009 Electronics, sensors and digital hardware; 4606 Distribute computing and systems software
- Full Text
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