Development of a Rule-Based Safety Checking System for Autonomous Heavy Construction Equipment

Highway and road construction and maintenance involve operations of heavy construction equipment consistently exposing workers to injuries and fatalities. Frequent collisions between heavy equipment and workers on foot cause many deaths and disabilities. A large portion of these work zone fatalities, such as being struck by equipment and caught in/between equipment, can be effectively prevented by automatically detecting objects around the equipment, determining their poses and movements, and eventually alerting operators and workers about unsafe situations. This study attempts to embed a situational awareness to heavy construction equipment by integrating sensing technologies into heavy construction equipment. This study developed a Robots Operating System (ROS)-based software program to determine the placement of multiple sensors ensuring 360-degree visibility around the equipment and process the sensor data into an accurate 3D representation of the work zone environment to detect predefined unsafe situations. The prototype safety monitoring system evaluated in a simulated road construction environment successfully detected the presences and locations of human workers around the equipment.