Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture

  • Daniel H. Stolfi
  • Enrique Alba
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8109)

Abstract

The aim of the work presented here is to reduce gas emissions in modern cities by creating a light infrastructure of WiFi intelligent spots informing drivers of customized, real-time routes to their destinations. The reduction of gas emissions is an important aspect of smart cities, since it directly affects the health of citizens as well as the environmental impact of road traffic. We have built a real scenario of the city of Malaga (Spain) by using OpenStreetMap (OSM) and the SUMO road traffic microsimulator, and solved it by using an efficient new Evolutionary Algorithm (EA). Thus, we are dealing with a real city (not just a roundabout, as found in the literature) and we can therefore measure the emissions of cars in movement according to traffic regulations (real human scenarios). Our results suggest an important reduction in gas emissions (10%) and travel times (9%) is possible when vehicles are rerouted by using the Red Swarm architecture. Our approach is even competitive with human expert’s solutions to the same problem.

Keywords

Application Evolutionary Algorithm Gas Emissions Road Traffic Smart City Smart Mobility 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniel H. Stolfi
    • 1
  • Enrique Alba
    • 1
  1. 1.LCCUniversity of MálagaSpain

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