Distributed Q-learning controller for a multi-intersection traffic network


Autoria(s): Araghi, Sahar; Khosravi, Abbas; Creighton, Douglas
Data(s)

01/01/2015

Resumo

This paper proposes a Q-learning based controller for a network of multi intersections. According to the increasing amount of traffic congestion in modern cities, using an efficient control system is demanding. The proposed controller designed to adjust the green time for traffic signals by the aim of reducing the vehicles’ travel delay time in a multi-intersection network. The designed system is a distributed traffic timing control model, applies individual controller for each intersection. Each controller adjusts its own intersection’s congestion while attempt to reduce the travel delay time in whole traffic network. The results of experiments indicate the satisfied efficiency of the developed distributed Q-learning controller.

Identificador

http://hdl.handle.net/10536/DRO/DU:30082483

Idioma(s)

eng

Publicador

Springer

Relação

http://dro.deakin.edu.au/eserv/DU:30082483/araghi-distributedqlearning-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30082483/araghi-distributedqlearning-evid1-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30082483/araghi-distributedqlearning-evid2-2015.pdf

http://www.dx.doi.org/10.1007/978-3-319-26532-2_37

Direitos

2015, IEEE

Palavras-Chave #Science & Technology #Technology #Computer Science, Artificial Intelligence #Computer Science, Theory & Methods #Computer Science #SIGNAL CONTROL #SIMULATION #MANAGEMENT #MODEL #TIME
Tipo

Conference Paper