A framework for traffic management and collision avoidance in underground mines

Abstract: Mining is an ancient occupation and the purpose is to access and extract minerals in the ground, which after being brought to the surface can be processed and sold at a profit. A mine, especially when active, is a dangerous place; mine collapse and other accidents have over the years claimed many lives. To improve the safety of personnel and equipment, there is an increased market for automating the vehicles operating in the mines. With no drivers in the vehicles, it is necessary to make sure the vehicles get to their goals without colliding with each other or perhaps with vulnerable personnel working in the mine. This can be done by performing traffic management. The traffic management is also important from a scheduling point of view; by planning where and when a vehicle should go to a certain part of the mine, the material flow can be optimized and so also the profit. This project has been carried out with the purpose of creating a framework to be used for simulating autonomous vehicles in underground mines. The framework is dynamic and supports e.g. fast map generation, and has an anticollision algorithm to prevent collisions when the simulated vehicles all try to go to different destinations in the map. With a total runtime of 100 hours using this framework, 2 total shutdowns have occurred (a state where all vehicles are stopped as a result from a pair of vehicles getting too close to each other) and 1 dead lock (a case where no collision has occurred, yet none of the vehicles could continue to their goal). Hence, due to the rarity of these, the conclusion that the overall concept of the collision avoidance algorithm seems to work has been made.