Please use this identifier to cite or link to this item:
Title: Study of correlation among several traffic parameters using evolutionary algorithms: traffic flow, greenhouse emissions and network occupancy
Authors: Medina, Javier Sánchez 
Moreno, Manuel Galán
Royo, Enrique Rubio 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Genetic algorithms
Cellular automata
Traffic optimisation
Greenhouse emission
Multicriteria optimisation
Issue Date: 2007
Project: Gestor de Conocimiento, Personal y Corporativo, Orientado A Procesos: Plataforma Suricata. 
Journal: Lecture Notes in Computer Science 
Conference: 11th International Conference on Computer Aided Systems Theory 
Abstract: During the last two years we have been working on the optimisation of traffic lights cycles. We designed an evolutionary, distributed architecture to do this. This architecture includes a Genetic Algorithm for the optimisation. So far we have performed a single criterion optimisation – the total volume of vehicles that left the network once the simulation finishes. Our aim is to extend our architecture towards a multicriteria optimisation. We are considering Network Occupancy and Greenhouse Emissions as suitable candidates for our purpose. Throughout this work we will share a statistical based study about the two new criteria that will help us to decide whether to include them or not in the fitness function of our system. To do so we have used data from two real world traffic networks.
ISBN: 978-3-540-75866-2
ISSN: 0302-9743
DOI: 10.1007/978-3-540-75867-9_142
Source: Moreno Díaz R., Pichler F., Quesada Arencibia A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg
Appears in Collections:Actas de congresos
Show full item record


checked on Apr 14, 2024


checked on Feb 25, 2024

Page view(s)

checked on Dec 23, 2023

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.