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In urban mobility, every minute counts. A breakdown during rush hour or an unexpected traffic jam can paralyze an entire city. The difference between chaos and fluidity lies in the ability to anticipate. That’s where Big Data becomes decisive: it transforms massive volumes of information into predictions and early alerts, allowing traffic managers to act before the problem spirals out of control.

A nearby example is Aimsun, a company born in Barcelona with global ambition, which has been developing traffic simulation software for decades. Its early versions were used to forecast the impact of roadworks or changes in traffic lights. Today, its solutions combine real-time data with predictive models to anticipate what will happen on the road network in the coming minutes or hours. In cities across Europe, Asia, and the U.S., Aimsun helps decide when to divert traffic, reinforce bus lines, or activate emergency plans.Los límites de los datos

The Limits of Data

But data is not a magic wand. As a researcher from Aimsun points out in a company blog article, a simple incident—like a broken-down truck—can be resolved quickly thanks to automatic incident detection. However, if that shifts passengers to public transport without prior coordination, the traffic jam in one area can move to another part of the city. The lesson is clear: isolated data is not enough; a holistic view is needed.

This is precisely the path outlined by the European Union (EU). In its report Inclusive and Sustainable Future of Urban Mobility (2025), it identifies the use of Big Data, analytics, and AI algorithms as one of the major trends for smarter urban mobility. It also adds a strategic recommendation: move toward integrated multimodal management—that is, coordinating different modes of transport (road traffic, public transport, bicycles) so that decisions are made with the entire network in mind, not just isolated parts.

Toward Integrated Management in Europe

The EU also promotes, according to this report, the creation of Mobility Data Spaces (MDS). What are they? Digital ecosystems where administrations, operators, and private platforms exchange real-time information. This way, a road incident can be instantly cross-referenced with data from metro, buses, or public bike services. The goal is to anticipate bottlenecks and coordinate responses across the entire network, rather than reacting late and separately.

Only cities that know how to read their data will achieve agile and people-friendly mobility.