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By Diego Giuliani
Published on
Autonomous heavy machinery and drones are joining forces to cut emissions and enhance safety in tunnel construction, thanks to a Spanish-led EU initiative.
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With the construction industry responsible for nearly 40% of global energy-related CO2 emissions, the carbon footprint of the materials and processes in a single major tunnel project can equal the emissions of hundreds of thousands of intercontinental flights.
With major works such as the Mediterranean Corridor in Spain and the Brenner Base Tunnel in the Alps currently underway, the adoption of low-carbon, high-efficiency solutions is becoming a priority for the sector.
In the hazardous atmosphere following a tunnel blast, visibility is near zero, and the risk of unexploded charges is a constant threat to human workers.
This is where the ‘BEEYONDERS’ project intervenes by removing the “human factor” from the danger zone.
The pilot site selected for this phase of the experimentation was the Fundación Santa Bárbara in Ribera de Folgoso, a former quarry now repurposed as a training and simulation facility for technical teams involved in construction, maintenance, and emergency response in north-western Spain.
This controlled environment allows researchers and engineers to safely test and refine autonomous systems under realistic conditions before deploying them in active infrastructure projects.
“We employ drones in two distinct stages,” explains Marco Montes Grova, Perception and AI Engineer at CATEC. “First, they map the tunnel to create a digital twin. Then, after the detonation, the drone serves as the loader’s eyes, guiding it through the smoke to the excavation front. Its thermal camera can even detect unexploded ordnance.”
The new tech saves time
This synergy doesn’t just save lives; it optimises the entire construction cycle. By allowing machinery to enter the tunnel immediately after a blast—while the air is still too thick for humans—the technology significantly reduces downtime.
The same autonomous loader technology is being adapted for surface works, with testing recently conducted at a pilot site along the Rome-L’Aquila highway in Italy.
Here, the autonomous loader operates within a sophisticated digital ecosystem. Drones perform photogrammetry to map the site and define the machine’s optimal path, while workers are equipped with wearable RTK sensors.
These sensors allow the loader to identify and avoid personnel in real-time, automatically stopping to ensure 100% safety on site.
“This mechanical loader, converted to autonomous driving, can cut fuel use by about 10% in a sector as energy-intensive as road construction,” says Fabrizio Federici, Project Manager at AISCAT Servizi. “The information collected allows the digital twin to calculate the best and safest route, directly reducing environmental pollution.”
By automating inspections and heavy lifting, both underground and on active highways, these innovations aim to transform infrastructure sites into high-precision, low-emission digital environments.
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