Big data contributing to improve road safety

With the increase in connected autonomous vehicles, road safety in the future will be defined by big data. In fact, we are already on the way towards the shift. Whenever we drive a connected car, dozens of gigabytes of data are generated randomly and collected by its numerous sensors and electronic components, such as traction control, stability control, the front camera, and radar.

For example, Google Maps accurately predicts the amount of traffic that lies ahead in our commute. For this to work perfectly, Google uses a ton of user data and machine learning algorithms to predict the estimated time of commute for each passenger, analyzing the route and traffic ahead.

"The first challenge for the Data Office team is to gather these large volumes of information. Then we have algorithms, mathematical and statistical techniques to process them and draw conclusions," says Carlos Buenosvinos, one of the people in charge. And it's all based on 100% anonymized data. 

Data from traction control, stability control, brakes, and our vehicles' temperature tell us about all those conditions that affect tyre contact with the road, from accumulated water, ice, or snow to broken or worn pavements. "With all this information we contribute to the generation of friction maps, which we can either share with navigation services that alert drivers to potential dangers on the road or with infrastructure operators who use them to ensure the proper maintenance of the road network," explains Víctor Monserrate, who also heads the SEAT Data Office. With the advent of autonomous cars and 5G, the generation of data will increase exponentially, and with it, the value we can extract in the form of new products and services.