Artificial intelligence

This is the way the technology works that will reduce traffic jams

13 of May of 2019

Mornings in traffic jams are a tremendous waste of time, but also of money. In the most congested cities, the amount can be as high as 20 billion dollars per year, and there are citizens who lose more than 100 hours a year stuck inside their vehicles.

Los Angeles, New York, Sao Paulo or Moscow. Very attractive cities for living or visiting but with a big problem, congestion. According to a study published in 2018 by transportation consultant INRIX, Los Angeles is the world’s city where the most time is spent in jams, specifically 102 hours during peak times in a year. On top of that, this great US city loses more than 19 billion dollars to gridlock every year. The figure for New York is even more striking. Here, although citizens waste less time (91 hours a year in traffic congestion), the city loses almost 34 billion dollars, or 3,000 dollars per driver, per year.

In Spain we don’t lag behind either. Madrid’s citizens spend some 42 hours a year in gridlock. In other words, according to Inrix, 13% of driving time is lost in jams. At a time when we are already talking about intelligent, self-driving cars and even drones capable of carrying passengers, how can we be wasting so much time and money on this?

The reality is that all these technologies are under development but we are still at a very early stage where, despite some products being in operation, we are still lacking the infrastructure and the technology still has to mature. You will surely have heard of Artificial Intelligence, Big Data, 5G or the Internet of Things, fundamental concepts for intelligent vehicles to help us reduce traffic congestion in the future.

In the transport industry, and even more so if we’re talking about driving in the future, the amount of data collected is indispensable. Thanks to Big Data, businesses in charge of infrastructure, automotive companies and drivers will have many more tools available for managing traffic. But how do we extract as much information as possible from our roadways?

Infographics Ferrovial is part of Madrid in motion

Another key technology, the Internet of Things or IoT, comes into play here. Consider the example of Carolina Osorio, a researcher at MIT who has been working for a few years on reducing traffic gridlock by 20% in New York City. To that end she collects information from cameras and sensors installed around the city in order to construct an algorithm, namely an intelligent template, to better understand traffic and improve the way it is managed. These sensors installed in roadways, either on lampposts, on traffic lights or on the vehicles themselves, turn them into intelligent objects, since they connect to the internet and, in this case, are able to collect information. These connected traffic lights or posts belong to the IoT universe.

The sensorizing of many of the roadways is augmented with the information that users are able to contribute. Simply via our cellphone signal we are reporting our exact location and with devices such as a smartwatch or smart wristband it is even possible to know whether we are sitting or standing. All this information emitted by each user, together with the data that may be emitted by streets and roads, amounts to such massive quantities of information that a new technology has to be brought on scene to, in this case, impose order. This is where artificial intelligence comes into its own.

The Alan Turing Institute and Toyota Mobility Foundation have been working since last year on an artificial intelligence platform (AI) capable of predicting and preventing traffic jams. Predicting? Yes, the great thing about artificial intelligence is its ability to analyze all the previously collected data in order to make it useful. In this case, this project being undertaken by the Institute and Toyota aims to implement an AI system to control traffic light signals, create a platform to monitor data and predict traffic progression, plus seek mechanisms for cities to collaborate by sharing information on the main focal points of congestion or pollution in order to offer alternative routes.

All right. And will the network withstand the transmission of so much data? Not for now, no. This is why there has been so much talk of 5G in recent years as the technology that will bring us super-fast navigation or will allow driverless cars to circulate. Imagine that a car has to decide between accelerating or braking based on a signal emitted by a traffic light and that information arrives too late. Not a second’s delay between sending the information and receiving it can be permitted on the road, since in that instant driver safety may be at stake. This is why 5G is expected to be the network that will allow all that information emitted by cars, signals, traffic lights and even roadways to be managed much more quickly, without any potential delays so as not to compromise road safety.

Many technologies at stake and a clear goal, attaining more intelligent roads on which our also-intelligent cars can circulate, and improving traffic and our safety. There are no dates yet, but it’s not far off.

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