Optimization of an autonomous vehicle dispatch system in an underground mine
The mining industry can greatly benefit from automation. A great deal of work has been
done on this subject and is still ongoing. With automation comes the possibility for
optimization, because more information is available, and actions can be repeated with
more accuracy. Many factors in an underground environment make mining automation
a challenging prospect. These factors include the difficulty and cost of installing the
needed infrastructure. The work described in this dissertation focuses on a mining setup
where vehicles such as LHDs and trucks are used to collect and transport ore
underground. Considerable progress has been made in automating underground
vehicles, and successful tests have been done underground. The next obvious step is to
find ways of using the increased data to optimize the decisions that are made with
regards to the dispatching of the vehicles.
Possible solutions to the problem of optimizing the autonomous vehicle dispatch system
in an underground mine are investigated. Possible optimization strategies are evaluated
using a simulated environment. In the simulated environment a block cave mine is
modelled, and the simulation setup is discussed in detail. The operation of a block cave
mine as it is operated currently is simulated to obtain a benchmark for the evaluation of
further results. The simulation results for the developed strategies are evaluated against
specific criteria, and indicate definite improvements on current methods used in mines.
Some important things that must be kept in mind for the physical implementation of the
dispatching strategies, as well as mining automation in general, are also discussed.