Design and evaluation of a Digital Twin-enabled IoV parking system for real-time guidance and resource optimization

This paper proposes a novel Digital Twin-enhanced Internet of Vehicles parking management system designed to address inefficiencies in traditional urban parking. The system features a four-layer architecture—perception, communication, platform, and application—enabling real-time sensing, intelligent guidance, and dynamic resource allocation. By using digital twin technology, it facilitates dynamic reservation and real-time parking guidance based on lot occupancy. Through simulation experiments, the proposed system demonstrates significant improvements in parking efficiency and resource utilization compared to baseline strategies. The results validate the potential of integrating digital twin technology with IoV infrastructure for more responsive and efficient parking management solutions, enhancing decision-making through feedback and optimization mechanisms.