COPIED
3 mins

PUSHYSIX

WHEN AUTONOMY STOPS BEING A PILOT AND STARTS BEING PRODUCTION

For years, autonomous haulage has lived in a familiar gray zone. Promising technology, impressive demos, controlled pilot projects, and plenty of caveats. It has been talked about far more than it has been trusted. With Pronto.ai, that line has now been crossed.

Story & Photography Scott Colclough Aka Pushysix

At Heidelberg Materials’ Lake Bridgeport quarry in Texas, autonomy is no longer an experiment. More than two million tons of limestone have already been hauled using fully autonomous trucks, and this is now the standard operating model at the site. Not a trial, not a test fleet, but day to day production.

This matters because production environments do not tolerate theory. Systems either work, or they create bottlenecks, safety risks, and downtime. Lake Bridgeport is operating at scale, and the results are difficult to ignore.

The operation runs a fleet of seven fully autonomous haul trucks working as a coordinated system rather than individual machines. The difference is immediately apparent. Material moves steadily without congestion. Trucks are not stacked up waiting to load. Blind corners are no longer a constant risk. Each truck is aware of the position and behavior of every other truck on the network.

Obstacle detection is not reactive, it is adaptive. When an object appears on the haul road, the system adjusts routing in real time and communicates the change across the entire fleet. What one truck encounters, all trucks learn from. The inefficiencies and uncertainty that typically slow production simply do not build up.

The result is a haulage operation that feels unusually calm. For anyone familiar with quarry or mining environments, that is a notable shift. Flow becomes predictable. Decision making moves from reactive to proactive. Productivity becomes repeatable rather than dependent on ideal conditions.

But the technical performance, while impressive, is only part of the story. The Lake Bridgeport deployment represents something the industry has struggled with for years: mixed fleet autonomy. Caterpillar and Komatsu haul trucks are operating together on the same autonomous network, without forcing the operation into a single OEM ecosystem.

This is a fundamental change

Historically, autonomy has come bundled with vendor lock in. Automation platforms were tied to specific brands, specific machines, and specific long term purchasing commitments. That model limited flexibility and often slowed adoption.

Pronto’s approach breaks that pattern. The system is brand agnostic, allowing operators to automate the iron they already own and make future purchasing decisions based on performance and fit, not software restrictions. For fleet owners, this shifts autonomy from a constraint to a strategic advantage.

From an operational standpoint, it also reduces complexity. There is no need to redesign the site around the technology. The technology adapts to the site. Dynamic loading zones, changing dump locations, and evolving production plans are handled without constant engineering intervention.

There is also a labor dimension that cannot be ignored. Across the aggregates and mining sectors, recruiting and retaining skilled haul truck operators is becoming increasingly difficult. Autonomous haulage changes how labor is deployed. Operators transition into higher value roles. Safety exposure is reduced. Consistency improves across shifts and seasons.

This is not about removing people from operations. It is about reallocating human effort where it delivers the most value.

What makes Lake Bridgeport significant is not just the milestone itself, but what it signals for the broader industry. Autonomy has moved past the stage where success is measured by hours run or distance traveled. It is now being measured in millions of tons moved under real production conditions.

“THIS IS NOT ABOUT REMOVING PEOPLE FROM OPERATIONS. IT IS ABOUT REALLOCATING HUMAN EFFORT WHERE IT DELIVERS THE MOST VALUE .”

This article appears in Issue 31

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Issue 31
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