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  5. Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion
 
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Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion

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Author(s)
Wang, Shen 
Djahel, Soufiene 
Zhang, Zonghua 
McManis, Jennifer 
Uri
http://hdl.handle.net/10197/11314
Date Issued
October 2016
Date Available
13T16:52:23Z March 2020
Abstract
During peak hours in urban areas, unpredictable traffic congestion caused by en route events (e.g., vehicle crashes) increases drivers' travel time and, more seriously, decreases their travel time reliability. In this paper, an original and highly practical vehicle rerouting system, which is called Next Road Rerouting (NRR), is proposed to aid drivers in making the most appropriate next road choice to avoid unexpected congestions. In particular, this heuristic rerouting decision is made upon a cost function that takes into account the driver's destination and local traffic conditions. In addition, the newly designed multiagent system architecture of NRR allows the positive rerouting impacts on local traffic to be disseminated to a larger area through the natural traffic flow propagation within connected local areas. The simulation results based on both synthetic and realistic urban scenarios demonstrate that, compared with the existing solutions, NRR can achieve a lower average travel time while guaranteeing a higher travel time reliability in the face of unexpected congestion. The impacts of NRR on the travel time of both rerouted and nonrerouted vehicles are also assessed, and the corresponding results reveal its higher practicability.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Transactions on Intelligent Transportation Systems
Volume
17
Issue
10
Start Page
2888
End Page
2899
Copyright (Published Version)
2016 IEEE
Keywords
  • Vehicles

  • Roads

  • Reliability

  • Routing

  • Multi-agent systems

  • Urban areas

  • Indexes

DOI
10.1109/tits.2016.2531425
Language
English
Status of Item
Peer reviewed
ISSN
1524-9050
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Computer Science Research Collection
Scopus© citations
93
Acquisition Date
Feb 1, 2023
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709
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Feb 1, 2023
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