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Intelligent transport as a means towards the sustainability of cities

Florence is being the scene of an important test for the Italian city to improve both mobility and sustainability. These are the smart trams, which are part of the ELASTIC project, funded by the European Union. Three of these vehicles of the public transport system carry a set of sensors such as cameras, inertial measurement units (IMU) – which report speed and orientation – radars or a LIDAR, a laser to determine the distance to an object.

For the correct information flow to be generated, it is necessary that the stops, three in the Italian city test, include devices with detection, computing and communication capabilities. The advances are aimed at giving the first clues about the smart cities of the future, which will have sustainability and the reduction of pollution as one of their main premises.

For Eduardo Quiñones, ELASTIC coordinator and researcher at the Barcelona Supercomputing Center, who coordinates the project, it is about offering an alternative to the user when the private autonomous vehicle is a reality. He considers that the question is to make “transport more agile, that the route can change, depending on the needs of both the people and what is happening in the city. The fundamental part is the data.”

Towards less polluting cities

The Florence experiment is working on creating smart zones, combining data from tram lines, city streets, and pedestrian crossings. The sustainability of cities is another of the objectives of this initiative.

The most obvious part is the decrease in the use of private vehicles, since even electric cars have an environmental implication, for example with the batteries they use. For this, it is necessary that public transport works in a way that convinces citizens of its advantages.

But there is another factor that influences the reduction of pollution. Internet and device use account for about 4% of total greenhouse gas emissions. Intelligent transportation requires highly precise computer equipment that requires a large amount of energy, so, according to Quiñones, it is a matter of “these artificial intelligence methods working in devices that do not require so much energy, to focus on efficient use with low-power devices “.

The next step for ELASTIC is for the information to be used to know the position of the tram, the presence of obstacles along the line and the tram stops, and the movement of citizens and vehicles.

But for that, a good network design is necessary, since the system is not centralized and “there are different computing nodes that have to coordinate to generate a common response. It is a challenge that computing has to address. real time “, explains the person in charge of the project.

ELASTIC aims to reduce the number of tram-related accidents in Florence by 25%, to have a 5% improvement in city traffic and to save 30% of maintenance costs in transport.

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