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Received 17.06.2025

Revised 23.10.2025

Accepted 27.11.2025

Retrieved from Vol. 29, No. 2, 2025

Pages 59 -70

  • 182 Views

Suggested citation

Lukhanin, V. (2025). Methodological principles for forming a simulation model of road-traffic management with dynamic redistribution of traffic flows. The National Transport University Bulletin, 29(2), 59-70. https://doi.org/10.33744/2308-6645-2025-2-29-59-70

Methodological principles for forming a simulation model of road-traffic management with dynamic redistribution of traffic flows

Volodymyr Lukhanin

Abstract

The aim of the study was to develop a conceptual model of two-level road-traffic management in urban transport networks. The methodology was based on structural-functional analysis and the application of a multi-level approach to managing transport flows. It was found that the initial stage of forming a simulation model involved formalising the street-road network and selecting a system of variables to describe its state over time. The state of the traffic flow was specified by indicators of density, traffic intensity, average speed, queue lengths and waiting time. In the proposed formulation, the road-traffic management system had two levels: routing and local traffic-signal control. Dynamic flow assignment was considered as a mechanism for adjusting routes for each origin-destination pair and setting traffic-signal phases, whereas local control was interpreted as regulating green-signal durations and coordinating the operation of traffic signals at intersections. Optimal control was oriented towards reducing delays and uneven network loading, taking into account the specified constraints. The control algorithm combining local and network regulation was interpreted as an approach aimed at improving network efficiency, ensuring optimal use of resources under variable demand and driver behaviour. The proposed architecture of a discrete-event simulation model for dynamic redistribution of transport flows was based on a stochastic dynamical system with discrete time. It integrated two control levels: local traffic-signal control and network control of routes for origin-destination pairs. The model specified an approach to adaptive flow distribution based on the current network state (queues, delays, traffic intensity) and made it possible to study the impact of route changes and traffic-signal control parameters on delays and network loading under stochastic demand fluctuations. The practical significance lies in the possibility of using the results by local authorities and road services as a methodological basis for designing and implementing simulation models of urban transport systems

Keywords:

dynamic system; adaptive algorithms; intersection; traffic-signal phase change; route optimisation; delay time

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