The Possibilities of Using Digital Twins to Predict the Bifurcation of Traffic Flow

The article discusses the possibilities of using digital twins to predict the bifurcation of the traffic flow. The use of digital twins at different levels of a nonlinear dynamic system makes it possible to stabilize its lifecycle. The system's abnormal states can be predicted by digital twins based on AI algorithms. But the possibilities of such analytics are limited by the large amount of data and calculations based on a traditional element base. A possible solution of the problem is to use neuromorphic computing devices in combination with a conventional element base. The analogue calculations nature allows for additional capabilities for real-time data analysis. That is especially important for making predictions of the behavior of quantities, which can lead to undesirable consequences for the state of the system. The purpose of this article is to explore the possibilities of preventing critical states of the system, such as bifurcation, using digital twins.