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Phdthesis3024

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Organic Traffic Control




Datum: 15. Juli 2011
KIT, Fakultät für Wirtschaftswissenschaften
Erscheinungsort / Ort: Karlsruhe
Referent(en): Hartmut Schmeck, Peter Vortisch
BibTeX


Kurzfassung
Modern cities cannot be imagined without traffic lights controlling their road network. To handle the network’s traffic efficiently, the traffic lights need to adapt their signalisation in response to changing demands. This requires shifting the signal plan specification from the design time to the run-time of the signal system.

This work builds on the generic observer/controller architecture proposed for Organic Computing to facilitate the shift. A two-levelled learning mechanism optimises an intersection’s signal plan on-line while a distributed coordination mechanism establishes progressive signal systems (or "green waves") in response to the current traffic demand. Thereby, delays and stops in the road network can be reduced such that fuel consumption rates and pollution emissions are lowered. The two-levelled learning mechanism is generally applicable to a wide area of safety- and performance-critical applications that have been inept for on-line optimisation before.


Projekt

OTCOTC2OTC3



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Organic Computing