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Reducing emergency services response time in smart cities: An advanced adaptive and fuzzy approach
Date Issued
2015-10-28
Date Available
2020-03-16T11:16:13Z
Abstract
Nowadays, the unprecedented increase in road traffic congestion has led to severe consequences on individuals, economy and environment, especially in urban areas in most of big cities worldwide. The most critical among the above consequences is the delay of emergency vehicles, such as ambulances and police cars, leading to increased deaths on roads and substantial financial losses. To alleviate the impact of this problem, we design an advanced adaptive traffic control system that enables faster emergency services response in smart cities while maintaining a minimal increase in congestion level around the route of the emergency vehicle. This can be achieved with a Traffic Management System (TMS) capable of implementing changes to the road network's control and driving policies following an appropriate and well-tuned adaptation strategy. This latter is determined based on the severity of the emergency situation and current traffic conditions estimated using a fuzzy logic-based scheme. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of our approach in terms of the significant reduction of emergency vehicles' response time and the negligible disruption caused to the non-emergency vehicles travelling on the same road network.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2015 IEEE
Web versions
Language
English
Status of Item
Peer reviewed
Part of
2015 IEEE First International Smart Cities Conference (ISC2)
Conference Details
The First IEEE International Smart Cities Conference (ISC2-2015), Guadalajara, Mexico, 25-28 October 2015
ISBN
9781467365529
This item is made available under a Creative Commons License
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Name
IEEE ISC2-2015 camear ready-6 October 2015.pdf
Size
780.58 KB
Format
Owning collection
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40
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