Listar por autor "Stolfi, Daniel H."
Mostrando ítems 1-6 de 6
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Un Algoritmo Evolutivo para la Reducción de Tiempos de Viaje y Emisiones Utilizando Paneles LED
Stolfi, Daniel H.; Alba-Torres, Enrique
(2015-02-09)
En este trabajo proponemos la arquitectura Yellow Swarm dedicada a la reducción de los tiempos de viaje del tráfico rodado mediante la utilización de una serie de paneles LED con el fin de sugerir diferentes cambios de ... -
An Evolutionary Algorithm to Generate Real Urban Traffic Flows
Stolfi, Daniel H.; Alba-Torres, Enrique (Springer International Publishing, 2015)
In this article we present a strategy based on an evolutionary algorithm to calculate the real vehicle ows in cities according to data from sensors placed in the streets. We have worked with a map imported from OpenStreetMap ... -
Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms
Stolfi, Daniel H.; Alba-Torres, Enrique (ACM, 2017-07)
GPS navigators are now present in most vehicles and smartphones. The usual goal of these navigators is to take the user in less time or distance to a destination. However, the global use of navigators in a given city could ... -
An Intelligent Advisor for City Traffic Policies
Stolfi, Daniel H.; Cintrano López, Christian; Chicano-García, José-Francisco; Alba-Torres, Enrique (2018-11-26)
Nowadays, city streets are populated not only by private vehicles but also by public transport, fleets of workers, and deliveries. Since each vehicle class has a maximum cargo capacity, we study in this article how ... -
Predicting Car Park Occupancy Rates in Smart Cities
Stolfi, Daniel H.; Alba-Torres, Enrique; Yao, Xin (Springer, 2017)
In this article we address the study of parking occupancy data published by the Birmingham city council with the aim of testing several prediction strategies (polynomial fitting, Fourier series, k-means clustering, and ... -
Red Swarm: Smart Mobility in Cities with EAs
Stolfi, Daniel H.; Alba-Torres, Enrique (ACM, 2013)
This work presents an original approach to regulate traffic by using an on-line system controlled by an EA. Our proposal uses computational spots with WiFi connectivity located at traffic lights (the Red Swarm), which are ...