A Multi-Agent based vehicles re-routing system for unexpected traffic congestion avoidance

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Title: A Multi-Agent based vehicles re-routing system for unexpected traffic congestion avoidance
Authors: Wang, ShenDjahel, SoufieneMcManis, Jennifer
Permanent link: http://hdl.handle.net/10197/11315
Date: Oct-2014
Online since: 2020-03-13T17:10:32Z
Abstract: As urbanization has been spreading across the world for decades, the traffic congestion problem becomes increasingly serious in most of the major cities. Among the root causes of urban traffic congestion, en route events are the main source of the sudden increase of the road traffic load, especially during peak hours. The current solutions, such as on-board navigation systems for individual vehicles, can only provide optimal routes using current traffic data without considering any traffic changes in the future. Those solutions are thus unable to provide a better alternative route quickly enough if an unexpected congestion occurs. Moreover, using the same alternative routes may lead to new bottlenecks that cannot be avoided. Thus a global traffic load balance cannot be achieved. To deal with these problems, we propose a Multi Agent System (MAS) that can achieve a trade-off between the individual and global benefits by giving the vehicles optimal turn suggestions to bypass a blocked road ahead. The simulation results show that our strategy achieves a substantial gain in average trip time reduction under realistic scenarios. Moreover, the negative impact of selfish re-routing is investigated to show the importance of altruistic re-routing applied in our strategy.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2014 IEEE
Keywords: VehiclesRoadResource managementNavigationEducational institutionsJunctionsCitiesTowns
DOI: 10.1109/itsc.2014.6958097
Language: en
Status of Item: Peer reviewed
Is part of: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
Conference Details: The 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), Qingdao, China, 8-11 October 2014
ISBN: 978-1-4799-6078-1
Appears in Collections:Computer Science Research Collection

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