EasyMine AI Tackles Groundbreaking Behavior Prediction for Safe and Efficient Mixed Traffic in Mining Autonomous Driving
Mining scenarios lack the structured features of typical roads, making traditional trajectory analysis methods difficult to handle the complex interactions of both human-driven and autonomous mining trucks. Compared to autonomous trucks, the trajectories of human-driven mining trucks change more frequently and diversely, leading to increased uncertainty and significantly increasing the difficulty of prediction and decision-making.
In 2025, the EACON team innovatively proposed the IMR (Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction) framework. This framework effectively distinguishes various behavioral patterns (such as overtaking, meeting, and avoiding), establishing clearer boundaries between these patterns. This provides more accurate predictions and decision-making support for autonomous mining trucks, improving the smoothness of vehicle interactions. This includes enhancing system safety, effectively reducing collision risks, and improving operational efficiency, thereby significantly driving the expansion of scenarios and improving overall business efficiency.
Currently, the algorithm version incorporating this trajectory prediction technology has been gradually deployed and has achieved significant results.
Improved adaptability to complex interactive scenarios: After deployment, this version significantly reduced travel time at mixed-traffic intersections at the No. 1 Open-Pit Coal Mine in the Yihua Wucaiwan Mining Area, enabling safe and smooth mixed operation with unmanned, human-driven mining trucks.
Optimized interactive behavior performance: Irrational braking behavior by autonomous mining trucks has been significantly reduced. Taking a typical unmanned coal mining scenario as an example, the frequency of heavy braking, medium braking, and light braking per unit mileage decreased by 10.0%, 43.2%, and 50.9%, respectively, reducing wear and tear on mining truck components.
Going forward, Easy Control Intelligent Driving will continue to deepen its research and development of core unmanned driving technologies to enhance the adaptability and operational efficiency of unmanned mining trucks in complex scenarios.
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