Study on the dynamics of traffic flow evolution in urban traffic networks

We address the challenges faced by urban transportation networks, particularly their susceptibility to congestion and the difficulty of recovery. A nearest-neighbor dual topological approach is employed to construct a comprehensive urban public transportation network. The study systematically considers key factors influencing the spread of congestion, such as temporal effects during the propagation process. By introducing congestion propagation rates and congestion recovery rates, the STIR propagation model is developed. This model reveals distinctive characteristics of urban traffic flow evolution and identifies the temporal patterns of traffic flow changes within transportation networks. The study focuses on analyzing the propagation and recovery dynamics of traffic flow evolution in transportation networks. Simulations on small-world and scale-free networks are conducted to validate the model. The effectiveness of the STIR model under the specified parameters is confirmed by comparing the simulation results with the actual traffic network evolution.