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

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Title: Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion
Authors: Wang, ShenDjahel, SoufieneZhang, ZonghuaMcManis, Jennifer
Permanent link: http://hdl.handle.net/10197/11314
Date: Oct-2016
Online since: 2020-03-13T16:52:23Z
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.
Funding Details: 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: VehiclesRoadsReliabilityRoutingMulti-agent systemsUrban areasIndexes
DOI: 10.1109/tits.2016.2531425
Language: en
Status of Item: Peer reviewed
Appears in Collections:Computer Science Research Collection

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