Digital Twin-Based Analysis of V2V Time-Varying Complex Networks

V2V technology is poised to play a crucial role in the future of the transportation sector, significantly transforming urban mobility. To analyze the dynamics and vulnerabilities of V2V technology, this paper develops a V2V time-varying complex network model grounded in time-varying complex network theory. The evaluation parameters chosen to analyze the dynamic topological characteristics of V2V time-varying complex networks include the clustering coefficient, average degree, average path length, and connectivity. Design deliberate and random attacks on network nodes to analyze the impact of various attack types and strengths on the destruction of V2V time-varying complex networks, thereby identifying the patterns of network vulnerability. For deliberate attacks, the selected node feature parameters include degree value, proximity centrality, betweenness centrality, and K-kernel centrality. To bridge theory and practice, this paper proposes a simulation framework for V2V scenarios based on digital twins and elaborates on the simulation methodology. Finally, the V2V scenario simulation is conducted using a case study based on real intersection traffic environments and actual traffic data. A V2V time-varying complex network model is constructed based on simulation data from a real intersection traffic scenario to facilitate the analysis of network dynamics and vulnerabilities.