Smart Mobility by Using Evolutionary Algorithms

Speaker:  Enrique Alba – Malaga, Spain
Topic(s):  Applied Computing

Abstract

Nowadays, cities are growing fast. Citizens are moving from the countryside to big cities looking for better jobs and services. As a consequence of this population growth, road traffic in cities is increasing, which is causing not only traffic jams, but also pollution and many diseases. 

In this lecture I present three different strategies to optimize road traffic: red swarm, green swarm, and yellow swarm. The first two consist of smart spots, usually installed at traffic lights, which suggest detours to drivers by using Wi-Fi connections, while the third one uses LED panels to achieve that objective. 

We will analyze several proposals in several case studies (Malaga, Stockholm, and Madrid), imported from OpenStreetMap into the SUMO traffic simulator. The presented strategies have proved to be useful for reducing travel times, greenhouse gas emissions, and fuel consumption of vehicles by preventing traffic jams, even when they are used by a reduced number of drivers. To this end, AI has been used, and evolutionary algorithms in particular, to get results that would represent a new state of the art in smart mobility.

These results are expected to help decision makers as well as workers in the mobility department of modern cities, thus making a real step (ideas, data, analysis, tools, technology) to shift from our present status to the a better one in which the whole city goes smarter.

About this Lecture

Number of Slides:  20
Duration:  30 minutes
Languages Available:  English, Spanish
Last Updated: 

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