Ponencia
Optimising Traffic Lights with Metaheuristics: Reduction of Car Emissions and Consumption
Autor/es | García Nieto, José Manuel
Ferrer, Javier Alba, Enrique |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2014 |
Fecha de depósito | 2021-05-11 |
Publicado en |
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ISBN/ISSN | 978-1-4799-1484-5 2161-4393 |
Resumen | In last years, enhancing the vehicular traffic flow
becomes a mandatory task to minimize the impact of polluting
emissions and unsustainable fuel consumption in our cities. Smart
Mobility optimisation emerges then, with ... In last years, enhancing the vehicular traffic flow becomes a mandatory task to minimize the impact of polluting emissions and unsustainable fuel consumption in our cities. Smart Mobility optimisation emerges then, with the goal of improving the traffic management in the city. With this aim, we propose in this paper an optimisation strategy based on swarm intelligence to find efficient cycle programs for traffic lights deployed in large urban areas. In concrete, in this work we focus on the improvement of the traffic flow with the global purpose of reducing contaminant emissions (CO2 and NOx) and fuel consumption in the analyzed areas. For the sake of standardization, we follow European Union reference framework for traffic emissions, called HandBook Emission FActors (HBEFA). As a case study, we have concentrated in two extensive urban areas in the cities of Malaga and Seville (in Spain). After several comparisons between different optimisation techniques (Differential Evolution and Random Search), as well as other solutions provided by experts, our proposal is shown to obtain significant reductions of fuel consumption and gas emissions. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España University of Ostrava Universidad de Málaga |
Identificador del proyecto | TIN2011-28194
BES-2012-055967 8.06/5.47.4142 |
Cita | García Nieto, J.M., Ferrer, J. y Alba, E. (2014). Optimising Traffic Lights with Metaheuristics: Reduction of Car Emissions and Consumption. En IJCNN 2014: International Joint Conference on Neural Networks (48-54), Beijing, China: IEEE Computer Society. |
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