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Royal Truck and Equipment Tests Vocational Autonomous Trucks on Florida Highway

Royal Truck and Equipment develops autonomous platooning technology for vocational and municipal applications such as sweepers, water trucks, line stripers, or maintenance trucks.

February 4, 2020
Royal Truck and Equipment Tests Vocational Autonomous Trucks on Florida Highway

Royal Truck and Equipment Royal, in collaboration with Kratos Defense,tested its Autonomous Truck Mounted Attenuator in a live demonstration on Florida's highways.

Photo: Royal Truck and Equipment 

2 min to read


Royal Truck and Equipment is a small, autonomous truck developer based in Coopersville, Pennsylvania, that specializes in platooning technology for vocational and municipal applications. The company says its autonomous control system can be used to operate a truck in a “Follower” mode when paired with a “Lead” vehicle.

Royal first developed this technology for use by the U.S. military and has since adapted it for the roadway construction industry through a partnership with Kratos Defense. The company said its technology can be added to any standard fleet vehicle such as sweepers, water trucks, line stripers, or maintenance trucks with either one, or multiple "Follower" trucks.

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On February 4, 2020, Royal, in collaboration with Kratos Defense, announced it would be putting its Autonomous Truck Mounted Attenuator (ATMA) technology to the test in a live demonstration on Florida's highways.

The company’s ATMA truck will be deployed in a live test operation spanning a 5-mile stretch of I-75 beginning near mile marker 160 and heading south.

During the live demonstration, the ATMA truck will support a mobile highway operation following behind a maintenance vehicle to provide protection from errant vehicles that might inadvertently enter the work zone. This is an autonomous leader-follower system consisting of a human-driven leader vehicle that transmits GPS data to the unmanned follower vehicle, which is the ATMA truck.  Advanced features include precision navigation, obstacle detection, and a number of operator-controlled parameters relevant to the operational environment in the lane closure.

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