MotoGP News

Ducati Incorporates Machine Learning to the MotoGP World Championship

Ducati learning



It’s the era of Big Data, artificial intelligence, machine learning algorithms. Nothing escapes the painstaking analysis of the gigantic data, and the MotoGP World Championship was not going to be less. Ducati sets out to open the Pandora’s box and put the bell to this digital cat. Will they achieve results as precise as those obtained by these disciplines in other fields?

The facts, as almost always, are much more explicit than the words themselves. Financial markets are nowadays taken by descriptive statistics, the analysis of stochastic processes and the development of algorithms that make their own decisions to buy or sell assets.

In baseball, the scrupulous study of myriads of player data was the starting point for applying new strategies to that sport, as was recounted in “Moneyball: Breaking the Rules”, the now famous movie played by Brad Pitt. More recently we have the example of Libratus, software created at Pittsburgh’s Carnegie Mellon University, which has pulverized a handful of professional poker players.

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It is no longer necessary to talk about Deep Blue and chess: machines are not only able to perform more calculations and more quickly but also learn from their opponents’ strategies and beat humans in games of skill and incomplete information. No wonder, therefore, that their participation in these competitions is prohibited.

Returning to the two wheels, what does Ducati propose then for this season? Firstly, the data analysis will allow them to obtain greater depth with many less tests on track, which means a significant saving of costs and time. In partnership with Accenture, they will apply their analysis to data obtained from more than 100 sensors, the internet of things, capable of capturing details such as engine parameters, speed, revolutions, brake temperature and tires. This information, combined with its own historical data, will allow Ducati to simulate results and its engineers optimize settings and configurations for different races and circuits.

Accenture understands that data visualization is going to become a key differentiator because of the analytical possibilities it offers. Marcello Tamietti, head of the Connected Transport division at Accenture Digital, notes that “the first results obtained are extremely promising”; And warns: “The data captured on the bikes during the first tests have allowed us to project several potential results depending on the settings applied. It starts a new line of debate among engineers about how to reach the ultimate goal: get the bike faster. ” The possibilities are unlimited: “engineers can use the knowledge thus obtained to test configurations in different simulated scenarios (rain, extreme heat …), transforming the way the Ducati Team applies its modus operandi, adding more value to work on the track, Performing smarter tests. ”

Luigi Dall’Igna, CEO of Ducati Corse, is hopeful about this new tool: “We have 18 Grand Prix races, and to make sure that our bike gives everything in each of them, we need to try out so many different configurations and scenarios As possible “. His words and enthusiasm sound promising to the overall followers of the red mark. Now we can only see if Jorge Lorenzo and Andrea Dovizioso are able to take advantage of this technological factor, incorporating what at the moment the machines are incapable of replacing: the genius, the human factor and the pilot skills.