Forecasting road traffic capacity using mathematical modeling of traffic flow dynamics

Abdullaevich, Mamadaliev Foziljon

Innovative Multidisciplinary Journal of Applied Technology · 2026-yil

Annotatsiya

The rapid growth of urbanization, motorization, and transportation demand has significantly increased the complexity of traffic management in modern cities. Accurate forecasting of road traffic capacity has therefore become a crucial task for transportation engineers, urban planners, and policymakers seeking to improve mobility, reduce congestion, and optimize infrastructure utilization. This study presents a mathematical modeling framework for predicting road traffic capacity based on fundamental traffic flow dynamics. The proposed approach employs the classical relationship between traffic flow, traffic density, and average vehicle speed and integrates an exponential speed–density function to describe nonlinear traffic behavior under varying congestion conditions. The mathematical model enables the determination of critical traffic density and maximum traffic throughput through analytical optimization of the flow–density relationship. Numerical simulations were conducted using a wide range of traffic density values to evaluate the model’s predictive performance and investigate congestion formation mechanisms. The simulation results demonstrate that traffic flow increases with density up to a critical threshold, beyond which traffic instability and congestion effects emerge, causing a reduction in operational efficiency. Furthermore, the model successfully reproduces the nonlinear characteristics of real traffic systems and provides physically interpretable estimates of roadway capacity. The findings indicate that the proposed modeling approach can serve as an effective tool for short-term and medium-term traffic forecasting, transportation planning, and intelligent transportation system applications. The model is computationally efficient, analytically transparent, and easily adaptable to various road network conditions. In addition, the framework creates opportunities for integration with real-time traffic monitoring technologies, sensor networks, and artificial intelligence algorithms. The proposed methodology contributes to the advancement of data-driven traffic management strategies and provides a practical foundation for improving road network performance, reducing congestion, and supporting sustainable urban transportation development.

Maqola ma’lumotlari
MualliflarAbdullaevich, Mamadaliev Foziljon
JurnalInnovative Multidisciplinary Journal of Applied Technology
NashriyotТДТУ Қўқон филиали
ISSN2995-486X, 2995-486x
Nashr sanasi2026-06-22
Jild4
Son6
Betlar40-46
TilIngliz
Ilmiy sohaTexnika
DOI10.51699/15fms907
Indeksga qo‘shilgan2026-08-26

DOI: 10.51699/15fms907 · Maqolaning asl sahifasi

Kalit so‘zlar

Road Traffic Capacity, Traffic Flow Dynamics, Traffic Capacity Forecasting, Mathematical Modeling, Traffic Density, Traffic Flow Theory, Congestion Analysis, Transportation Engineering, Intelligent Transportation Systems (ITS), Traffic Simulation, Urban Traffic Management, Roadway Performance Evaluation, Nonlinear Traffic Models, Transportation Planning, Traffic Optimization

Ilmiy soha

Texnika

Iqtibos keltirish

APAAbdullaevich, Mamadaliev Foziljon (2026). FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS. Innovative Multidisciplinary Journal of Applied Technology, 4(6), 40-46. https://doi.org/10.51699/15fms907
GOST (OAK)Abdullaevich, Mamadaliev Foziljon FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS // Innovative Multidisciplinary Journal of Applied Technology. – 2026. – T. 4, № 6. – P. 40-46. – DOI: 10.51699/15fms907.
MLAAbdullaevich, Mamadaliev Foziljon. “FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS.” Innovative Multidisciplinary Journal of Applied Technology, 4(6), 40-46, 2026. https://doi.org/10.51699/15fms907
ChicagoAbdullaevich, Mamadaliev Foziljon. “FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS.” Innovative Multidisciplinary Journal of Applied Technology, 4(6), 40-46 (2026). https://doi.org/10.51699/15fms907
HarvardAbdullaevich, Mamadaliev Foziljon (2026) ‘FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS’, Innovative Multidisciplinary Journal of Applied Technology, 4(6), 40-46. https://doi.org/10.51699/15fms907
BibTeX
@article{abdullaevichmamadalievfoziljon2026,
  title = {FORECASTING ROAD TRAFFIC CAPACITY USING MATHEMATICAL MODELING OF TRAFFIC FLOW DYNAMICS},
  author = {Abdullaevich, Mamadaliev Foziljon},
  journal = {Innovative Multidisciplinary Journal of Applied Technology},
  year = {2026},
  volume = {4},
  number = {6},
  pages = {40-46},
  doi = {10.51699/15fms907},
  url = {https://doi.org/10.51699/15fms907}
}

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