Preventing haul truck-related fatalities in open pit mining using gamified training simulation

Master thesis (2023)

Authors

L.G. Vos Civil Engineering & Geosciences

Contributors

M. Soleymani Shishvan Resource Engineering - CEG (supervisor 1)
M.W.N. Buxton Resource Engineering - CEG (supervisor 2)
Mikael Rinne Aalto University (supervisor 1)
Bernd Lottermoser Rheinisch-Westfälische Technische Hochschule (supervisor 1)
Faculty
Civil Engineering & Geosciences
Copyright: © 2023 Lennart Vos
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Published Date

21-12-2023

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Haul truck driving remains to be the most dangerous occupation in the mining industry (Kecojevic et al., 2007), leading in fatalities over other occupations in the mining industry. As the transition to autonomous haul trucks over the coming decades will not address thisproblem today, an immediate solution is needed that can be adopted at short notice to help aid in minimizing haul truck accidents. A gamified training simulator was developed that teaches haul truck drivers how to handle the hazardous situations that lead to the most injuries in the mine environment. The simulated nature of the training method allows truck drivers to gain knowledge on hazardous situations and immediately put them into practice by applying the gained knowledge during the different levels. Gamification aspects like a score system and progression through levels were added to increase engagement during the training simulation.
A statistical analysis was made on haul truck accidents from 1983 until 2022. The accidents that proved to be most relevant were included in the content of the training software. A training software was developed using Unreal Engine 5, where trucks could be driven using a Thrustmaster T150 Pro steering wheel and driving pedals. 18 participants from ages 19-65 underwent the training program and two tests of identical difficulty were taken before and after undergoing the training, in order to make a judgement on the progress of the participants by undergoing the training simulation. Participants were judged based on the number of crashes and traffic violations committed, attempts required to complete the test, as well as the time taken to finish the test. A score was calculated based on these factors providing an overall judgement of the participants’ level of skill.
Average skill of participants increased by undergoing the gamified training, and training showed particularly good progress for underperformers in the initial test. After completing the gamified training the average score of participants was notably higher and the standard deviation was notably lower. It was concluded that all participants were brought to a comparably high level after completing the training.