Modeling Traffic Flows Using Neural Networks
https://doi.org/10.21122/2227-1031-2025-24-4-317-326
Abstract
The object of the study is the process of traffic flows on the urban street and road network of a metropolis. Due to increasing urbanization, its negative consequences are also increasing, including a decrease in the speed of communication, leading to the formation of traffic congestion. The aim of the work is to develop a mathematical apparatus for controlling congested traffic flows on the urban road network using neural networks. The results of the study are aimed at sol- ving the problem of traffic congestion in cities, especially in the largest ones. The methodological basis of the research includes a systematic approach, systems analysis, synthesis, theories of traffic flows, systems, dynamic systems, complex systems and chaos. The objective function of the study is to maximize the kinetic energy of the transport flow. As an optimization criterion, it is proposed to use a measure of traffic chaos – the entropy of traffic flows. According to the results of the study, a mathematical model was obtained for changing the kinetic energy of the traffic flow under
About the Authors
V. V. Morozov
Industrial University of Tyumen
Russian Federation
Russian Federation
Tyumen
E. M. Chikishev
Industrial University of Tyumen
Russian Federation
Russian Federation
Tyumen
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For citations:
Morozov V.V., Chikishev E.M. Modeling Traffic Flows Using Neural Networks. Science & Technique. 2025;24(4):317-326. (In Russ.) https://doi.org/10.21122/2227-1031-2025-24-4-317-326
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