A Simulation-Based Decision-Support Framework for EV Charging Infrastructure Development Along a TEN-T Corridor

The rapid growth of electromobility is increasing pressure on charging infrastructure along major transport corridors. However, existing studies rarely combine corridor-scale microscopic traffic simulation with stochastic charging-demand modeling for both passenger cars and heavy-duty vehicles in order to assess the operational adequacy of charging infrastructure on TEN-T routes. This study presents a simulation-based decision-support framework for the staged development of EV charging infrastructure along the S19 Rzeszów–Barwinek section, a 90 km corridor forming part of the TEN-T and Via Carpathia networks. The methodology combines microscopic traffic simulation in PTV Vissim with probabilistic charging-demand modeling for passenger cars and heavy-duty vehicles. The novelty of the study lies in the integration of corridor-scale microscopic simulation, stochastic charging-demand representation, and planning-oriented infrastructure assessment within a unified framework. Three EV penetration scenarios were analyzed: 10%, 25%, and 45% of the traffic stream. Infrastructure utilization increased from approximately 95–100% in the 10% EV scenario to more than 120% in the 45% scenario, with queue length rising from about 0.2–0.8 to 1–3 vehicles per MOP and unmet charging demand reaching approximately 3–3.5 vehicles per MOP in the most critical periods. Heavy-duty EVs were identified as the dominant operational bottleneck due to longer charging times and limited charger availability. The proposed framework supports adaptive and scenario-based planning of corridor charging infrastructure beyond minimum regulatory requirements.