Computational intelligence-based traffic signal timing optimization


Autoria(s): Araghi, Sahar
Contribuinte(s)

Creighton, Douglas

Khosravi, Abbas

Johnstone, Michael

Resumo

 Traffic congestion has explicit effects on productivity and efficiency, as well as side effects on environmental sustainability and health. Controlling traffic flows at intersections is recognized as a beneficial technique, to decrease daily travel times. This thesis applies computational intelligence to optimize traffic signals' timing and reduce urban traffic.

Identificador

http://hdl.handle.net/10536/DRO/DU:30082933

Idioma(s)

eng

Publicador

Deakin Univeristy, Centre for Intelligent Systems Research

Relação

http://dro.deakin.edu.au/eserv/DU:30082933/araghi-agreement-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30082933/araghi-computationalintelligence-2015A.pdf

Direitos

The Author. All Rights Reserved

Palavras-Chave #traffic congestion #traffic flows #computational intelligence #traffic signal timing
Tipo

Thesis

Data(s)

31/12/1969