A Multi-Agent Based Vehicles Re-routing System for Unexpected Traffic Congestion Avoidance

Shen Wang, Soufiene Djahel, Jennifer McManis

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

47 Citations (Scopus)

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.

Original languageEnglish
Title of host publication17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2541-2548
Number of pages8
ISBN (Electronic)9781479960781
DOIs
Publication statusPublished - 20 Nov 2014
Externally publishedYes
Event17th International IEEE Conference on Intelligent Transportation Systems - Qingdao, China
Duration: 8 Oct 201411 Oct 2014

Publication series

Name
PublisherIEEE
ISSN (Print)2153-0009
ISSN (Electronic)2153-0017

Conference

Conference17th International IEEE Conference on Intelligent Transportation Systems
Country/TerritoryChina
CityQingdao
Period8/10/1411/10/14

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