Abstract
The present document explores how air pollution can be assessed from a multiagent point of view. In order to do so, a traffic system was simulated using agents as a way to measure if air pollution levels go down when the traffic lights employ a multigent cooperative system that negotiates the green light duration of each traffic light, in order to minimize the time a car has to wait to be served in an intersection. The findings after running some experiments where lanes of each direction are congested incrementally showed, that using this technique, there is a significant decrease in air pollution over the simulated area which means that traffic lights controlled by the multiagent system do improve the levels of air pollution.
This research has been supported in part by the ITESM Research Chair CAT-011.
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© 2005 Springer-Verlag Berlin Heidelberg
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Domínguez, J.H., Fernández, L.M., Aguirre, J.L., Garrido, L., Brena, R. (2005). Air Pollution Assessment Through a Multiagent-Based Traffic Simulation. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_30
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DOI: https://doi.org/10.1007/11579427_30
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