Whatever the risk on a motorway — an incident, a queue forming, or a sudden drop in visibility — the first line of defence is almost always the same: getting accurate information to the driver quickly enough for it to matter. Across all the MATIS’ project, this principle takes different forms depending on the corridor and the hazard involved.
SCT: connecting a whole network around Barcelona
Around Barcelona, Servei Català de Trànsit (SCT) built its project around a single question: how does a driver find out what’s happening on the road ahead quickly enough to act on it? Deployed across roughly 200 km of the busiest routes surrounding Barcelona and Baix Llobregat, the answer combines several channels feeding into one another. New Variable Message Panels deliver real-time updates directly to drivers, while advanced CCTV cameras with AI capabilities detect incidents the moment they happen — turning raw video into the trigger for the information a driver sees on the road.
The link between detection and communication is what makes this project distinctive. Rather than treating cameras and signage as separate systems, SCT routes everything through the CIVICAT Control Centre: an incident spotted by a camera can inform the message displayed on a panel further down the same route, often before the driver even reaches the affected section. Modern speed monitoring equipment adds a further layer, feeding data back into the same network while also discouraging the risky driving that so often causes incidents in the first place. The result is less a collection of separate tools than a single feedback loop — see, decide, inform — repeated continuously across the corridor.
ADF: turning footage into a number drivers can use
Where SCT took a network-wide view, Autostrada Dei Fiori (ADF) focused on a specific, well-defined stretch: 9 km of the A6 Torino-Savona motorway. Here, the starting point is the driver’s immediate need: knowing what conditions look like on the exact section they’re about to enter. The project installed 17 cameras in both directions to capture that picture in real time; many of them use artificial intelligence and algorithmic processing to calculate individual and average travel times automatically, converting raw footage into a figure a driver can use to judge their journey.
The travel time data feeds into both “in itinere” and external variable message signs positioned along the route, giving drivers a concrete answer: not just “there is an incident ahead” but “here is what your journey through this section will look like.” The underlying logic is identical as the previous project: better images, processed faster, translate into more precise information reaching the driver at the moment it’s still useful.
Autovia Padana: guiding drivers through a single hazard
The third project narrows the focus even further, addressing not a corridor’s overall traffic picture but one specific and often underestimated danger: fog. On the A21 Piacenza-Cremona-Brescia motorway, an anti-fog device has replaced traditional passive orange reflectors with active LED signs positioned every 25 metres along the central divider. Rather than relying on a vehicle’s headlights to catch a static reflector — something that fog itself can defeat — the new yellow/amber LED edge delineators create a continuous, actively lit guide along the route, managed centrally by the Traffic Control Centre.
The goal here is to reduce secondary accidents caused specifically by poor-visibility conditions, and by extension cutting the congestion, lost vehicle-hours and CO2 emissions that these secondary incidents generate. It’s a reminder that not every real-time information system needs cameras or AI to be effective — sometimes, a clearly lit path is enough to keep drivers safely on course.