These insights can help drivers adapt their driving styles for greater efficiency. From a practical perspective, early predictions combined with model-generated recommendation give drivers sufficient time to modify their trip based on terrain, driving style, or charging strategies, allowing for more informed decision-making. This creates a closed-loop optimization between driver and model, which fosters trust in predictive feedback and reduces range anxiety.