Phase transition in lattice hydrodynamic model integrating random anomalous information under connected autonomous vehicles surroundings

As vehicle-to-everything (V2X) communication technology rapidly evolves, connected autonomous vehicles (CAVs) have emerged as a significant component of traffic flow. However, anomalies in the information within the V2X environment can greatly impact the stability of traffic flow composed of CAVs. In this context, we have innovatively constructed a lattice hydrodynamic model by incorporating random anomalous information parameters. This model examines the effect of random anomalous information on the queue of CAVs within the V2X environment, capturing the interference of such information on traffic flow. Furthermore, we conduct linear stability analysis and nonlinear analysis for the new model, successfully deriving the neutral stability conditions and the modified Korteweg-de Vries (mKdV) equation. Additionally, through simulations, we explore the impact of random anomalous information on CAVs from the perspectives of density variation and density differences (limit cycle). Power spectrum and spectral entropy are also applied to investigate traffic stability and complexity under the interference of random anomalous information in the vicinity of CAVs. The simulation results indicate that an increase in the probability of information anomalies significantly degrades the stability of traffic flow, while variations in different anomalous information intensity coefficients produce heterogeneous disturbances in traffic flow dynamics.