The growing phenomenon of traffic congestion in urban areas, due to increasing motorization rates, has significant social, economic and environmental impacts. High vehicle congestion results in longer travel times and reduced accessibility to Points of Interests (POIs), especially during peak hours. While traditional strategies have prioritized infrastructure development, recent policies targeting the reduction of avoidable car journeys have shown some success in decreasing vehicle flows. However, it is crucial that these policies also develop measures to improve the accessibility of those who are dependent on the private car for their mobility due to the lack of modal alternatives, still existing in many areas. To address these issues, a comprehensive approach is proposed based on microsimulation of vehicle flows, developing a small-scale digital twin, to replicate daily operating conditions. The methodology consists of several steps: (i) supply reconstruction through microsimulation model, (ii) demand analysis driven by advanced surveys and sensor technologies, (iii) evaluation of intervention scenarios aimed at optimizing the use of resources and minimizing infrastructure interventions. The application of this methodology, tested on a real case study, consists of a main road in the urban area of Catania, characterised by high traffic volumes due to its strategic position and the presence of two attractive poles. It shows how targeted interventions, such as the improvement of road signs and the optimized management of car park entrances, can be effective solutions for improving accessibility and vehicle movements. Future developments will extend the model to assess the impact on the surrounding road network and to evaluate long-term interventions.