NDLI: Reducing emergency services response time in smart cities: An advanced adaptive and fuzzy approach

Content Provider	IEEE Xplore Digital Library
Author	Djahel, S. Smith, N. Shen Wang Murphy, J.
Copyright Year	2015
Description	Author affiliation: Sch. of Comput. Sci. & Inf., UCD, Dublin, Ireland (Djahel, S.; Smith, N.; Murphy, J.) \|\| Sch. of Electron. Eng., Dublin City Univ., Dublin, Ireland (Shen Wang)
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.
Starting Page	1
Ending Page	8
File Size	1416650
Page Count	8
File Format	PDF
e-ISBN	9781467365529
DOI	10.1109/ISC2.2015.7366151
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-25
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Smart cities Emergency Services Roads Smart Transport Road Traffic Congestion Cities and towns Smart Cities Emergency services Time factors Vehicles Traffic Management Systems (TMS)
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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