@article{Yan2025, 
author = {Huining Yan and Meihui Song and Hua Li and Qiubai Sun},
title = {Research on the propagation mechanism of traffic congestion warning information with random interference},
year = {2025},
journal = {AIMS Mathematics},
volume = {10},
number = {9},
pages = {21774-21793},
keywords = {congestion warning information, stochastic SEIR model, random parametric perturbations, optimal stochastic control strategy, traffic congestion},
url = {https://www.sciopen.com/article/10.3934/math.2025968},
doi = {10.3934/math.2025968},
abstract = {In social systems, information dissemination is affected by environmental factors. Moreover, positive information can promote social development. Therefore, a stochastic SEIR model was proposed to study the mechanism of traffic congestion warning information dissemination. In this article, we proved the existence of global positive solutions and the extinction of information, and proposed sufficient conditions for stationary distributions. Based on the Hamiltonian function, an optimal stochastic control strategy for the random propagation model was proposed. The numerical simulation results indicated that the theoretical results could be validated and compared with deterministic models. Adding random interference could promote the propagation of congestion information, it could promote the propagation of information, and better control traffic congestion. The volatility of congestion warning information propagation became more apparent with the increase of random disturbance intensity. By controlling random parameters, the propagation of congestion warning information could be effectively controlled, thereby controlling congestion. Moreover, the propagation effect of the proposed optimal stochastic control strategy was better than that of the random model, which verified the effectiveness of the proposed optimization control strategy.}
}