With the increasing number of private vehicles in urban agglomerations and growing freight traffic, there is a need to implement intelligent transportation systems to develop strategies to reduce congestion and prevent traffic accidents. One of the key indicators of the transportation system, reflecting the efficiency of using the available urban infrastructure, is the capacity of planned routes. The model for estimating the capacity of an urban route based on the capacity of its elements - runs and intersections - is multi-level, hierarchical, and multi-criteria. In addition, this model is dynamic because its parameters change over time. All this increases the computational complexity of analyzing such a model, and leads to the need to reduce the number of parameters under study. One approach to reducing model parameters is sensitivity analysis based on finite change analysis. In the case of the capacity model, this approach will allow to identify those parameters of the route elements, the change of which causes the greatest changes in the capacity of the route as a whole, and will give the opportunity to manage them in order to improve the overall efficiency of the system.The aim of the study is to develop a methodology for hierarchical sensitivity analysis of the capacity model of the street and road network based on finite change analysis, which makes it possible to identify critical points and assess the contribution of individual elements and groups of objects to the overall performance of the transportation system. The results obtained show that the proposed methodology allows to accurately identify the main factors affecting the capacity and to propose measures to optimize traffic flow management.

hierarchical sensitivity analysis, capacity, traffic flows, mathematical modeling, critical points, traffic flow management.