In current modern cities, the increasing number of traffic lights that control the vehicular traffic flow requires a highly complex scheduling. Thousands of red lights, that have to be optimally programmed, are nowadays operating in congested urban areas. Therefore, automatic intelligent systems are indispensable tools for optimally tackling this task. In this work, we propose a Swarm Intelligence approach that, coupled with the SUMO traffic simulator, is able to find successful cycle programs of traffic lights for large urban areas. In concrete, we have focused on a metropolitan area of the city downtown of Córdoba (in Spain). The experiments and comparisons with other techniques reveal that our proposed approach obtains significant profits in terms of traffic flow and global trip time.