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|Title=Decentralised Progressive Signal Systems for Organic Traffic Control | |Title=Decentralised Progressive Signal Systems for Organic Traffic Control | ||
|Year=2008 | |Year=2008 | ||
| + | |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 | ||
| − | |Projekt= | + | |Projekt=OTC,OTC2, |
| − | |Forschungsgruppe= | + | |Forschungsgruppe=Effiziente Algorithmen |
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{{Forschungsgebiet Auswahl | {{Forschungsgebiet Auswahl | ||
|Forschungsgebiet=Organic Computing | |Forschungsgebiet=Organic Computing | ||
}} | }} | ||
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