Mining haul trucks consume approximately 32% of total energy and account for up to 22% of operating costs in open-pit mines. 

Fuel consumption can be affected by equipment condition and characteristics, road design and conditions, weather conditions and driving behaviour, among others. 

Using data collected from sensors installed on haul trucks, the effect of important factors such as travel speed, road inclination, payload and weather conditions on fuel consumption is studied. 

Supervised machine learning modelling, followed by scenario analyses are used to support decision-making related to mine operation, maintenance and design. 

Our findings suggest strategies such as payload and maximum speed limit adjustments can yield significant fuel savings.