This study presents an Integer Linear Programming (ILP) model to optimize the dynamic allocation of drivers in European road transport companies, ensuring compliance with regulatory requirements on driving time, mandatory breaks, and minimum rest periods. These constraints are designed to enhance road safety and driver well-being. The proposed model integrates optimization techniques with the OR-Tools library, incorporating these regulatory rules along with dynamic interactions between drivers and customer demands. An interactive interface was implemented to enable sensitivity analysis and scenario simulations across different planning horizons. The proposed approach aims to support strategic and flexible decision-making, allowing rapid adaptation to variations in demand or operational and regulatory conditions. The results demonstrate efficiency in driver scheduling, reducing the total number of assigned drivers while maintaining full compliance with prevailing regulations. The model’s flexibility also enables its application to large-scale operations, such as international logistics networks and continuous transport systems. Furthermore, the adopted formulation is based on well-established workforce scheduling methodologies, extending its applicability to the specific context of European road transport.