The mining industry is moving towards increased autonomy, driven by the introduction of innovative technologies such as IoT, AI, machine learning, and big data. The integration of automation and intelligence forms the core of the Smart Mine framework, enabling autonomous systems that improve efficiency, enhance safety, and reduce environmental impact. However, the impact of these systems on mining operations remains underexplored. Unlike the automotive industry, where self-driving vehicles have made progress, mining environments pose unique challenges due to their unpredictable nature, limiting widespread adoption. However, the controlled environments of mining operations offer an ideal testing ground for autonomous vehicles. One emerging solution is the Digital Twin concept, which provides a dynamic model of a physical system throughout its operational life. By applying AI and machine learning, the Digital Twin can predict the evolution of the physical system and adjust mission plans accordingly. Key goals include converting conventional heavy trucks into autonomous units operating in convoy, developing a data-driven digital twin supported by site mapping technologies, deploying an IoT-based infrastructure for information sharing, and enabling self-evolutionary capabilities to improve performance over time.