Optimisation of traffic congestion model based on improved RIME

With the continuous growth of the number of motor vehicles, traffic congestion on urban roads, especially at intersections, is becoming more and more serious and shows obvious propagation effects. It is of great significance to study the law and scope of congestion propagation at intersections for effective traffic management. Based on floating vehicle trajectory data, this paper comprehensively analyses the network characteristics and traffic characteristics to comprehensively assess the intersection access efficiency, and adopts the fuzzy K-mean clustering method to grade the intersection efficiency, in order to explore the differences between different grades of intersections in terms of congestion propagation speed. Further, an infectious disease model is introduced in this paper to construct a congestion propagation model optimised based on Adaptive weights rime algorithm (AWRIME), which improves the simulation accuracy of congestion propagation in traffic networks. The results show that the proposed model is superior in both accuracy and adaptability of congestion propagation.