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|Title=Decentralised Progressive Signal Systems for Organic Traffic Control
 
|Title=Decentralised Progressive Signal Systems for Organic Traffic Control
 
|Year=2008
 
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|Month=Oktober
 
|Booktitle=Proceedings of the 2nd IEEE International Conference on Self-Adaption and Self-Organization (SASO 2008)
 
|Booktitle=Proceedings of the 2nd IEEE International Conference on Self-Adaption and Self-Organization (SASO 2008)
 
|Editor=Sven Brueckner and Paul Robertson and Umesh Bellur
 
|Editor=Sven Brueckner and Paul Robertson and Umesh Bellur
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learning capabilities. The efficiency of the resulting organic
 
learning capabilities. The efficiency of the resulting organic
 
system is demonstrated in a simulation-based evaluation.
 
system is demonstrated in a simulation-based evaluation.
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|Link=http://dx.doi.org/10.1109/SASO.2008.31
 
|Link=http://dx.doi.org/10.1109/SASO.2008.31
 
|DOI Name=10.1109/SASO.2008.31
 
|DOI Name=10.1109/SASO.2008.31
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|Forschungsgebiet=Organic Computing
 
|Forschungsgebiet=Organic Computing
 
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Aktuelle Version vom 11. September 2009, 14:59 Uhr


Decentralised Progressive Signal Systems for Organic Traffic Control


Decentralised Progressive Signal Systems for Organic Traffic Control



Published: 2008 Oktober
Herausgeber: Sven Brueckner and Paul Robertson and Umesh Bellur
Buchtitel: Proceedings of the 2nd IEEE International Conference on Self-Adaption and Self-Organization (SASO 2008)
Seiten: 413-422
Verlag: IEEE

Referierte Veröffentlichung

BibTeX

Kurzfassung
An increased mobility and the resulting rising traffic demands lead to serious congestion problems in many cities. Although there is not a single solution that will solve traffic congestions and the related environmental and economical problems, traffic light coordination is an important factor in achieving efficient networks. This paper presents a new distributed approach for dynamic traffic light coordination that relies on locally available traffic data and communication among neighbouring intersections. The coordination mechanism is combined with an organic traffic control approach to form an adaptive, distributed control system with learning capabilities. The efficiency of the resulting organic system is demonstrated in a simulation-based evaluation.

Weitere Informationen unter: Link
DOI Link: 10.1109/SASO.2008.31

Projekt

OTCOTC2



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Organic Computing