IoT-based emergency vehicle services in intelligent transportation system
Article
Chowdhury, A., Kaisar, S., Khoda, M., Naha, R., Khoshkholghi, A. and Aiash, M. 2023. IoT-based emergency vehicle services in intelligent transportation system. Sensors. 23 (11). https://doi.org/10.3390/s23115324
Type | Article |
---|---|
Title | IoT-based emergency vehicle services in intelligent transportation system |
Authors | Chowdhury, A., Kaisar, S., Khoda, M., Naha, R., Khoshkholghi, A. and Aiash, M. |
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 | Intelligent Transportation System; Emergency Vehicle Priority; Drone in Emergency; Electrical and Electronic Engineering; Biochemistry; Instrumentation; Atomic and Molecular Physics, and Optics; Analytical Chemistry; Travel; Transportation; Ambulances; Computer Simulation; Emergency Medical Services |
Sustainable Development Goals | 11 Sustainable cities and communities |
Middlesex University Theme | Sustainability |
Publisher | MDPI AG |
Journal | Sensors |
ISSN | |
Electronic | 1424-8220 |
Publication dates | |
Online | 04 Jun 2023 |
04 Jun 2023 | |
Publication process dates | |
Deposited | 05 Jun 2023 |
Submitted | 13 May 2023 |
Accepted | 01 Jun 2023 |
Output status | Published |
Publisher's version | License |
Copyright Statement | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. |
Digital Object Identifier (DOI) | https://doi.org/10.3390/s23115324 |
PubMed ID | 37300051 |
PubMed Central ID | PMC10256047 |
Web of Science identifier | WOS:001004687900001 |
National Library of Medicine ID | 101204366 |
Language | English |
https://repository.mdx.ac.uk/item/8q66y
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