Authors: Dr. Aniket V. Kale, Prof. Neha P. Trivedi
Abstract: Urban congestion has become a pressing concern for transportation planners and policymakers, as growing populations and increased vehicle ownership intensify pressure on road infrastructure. This paper investigates recent advancements in traffic flow modeling and simulation, with a special focus on predictive and mitigation strategies for congestion in urban environments. Through a comprehensive review of deterministic and stochastic models, microscopic and macroscopic simulations, and AI-based traffic forecasting methods, this study highlights how modern tools are reshaping urban mobility. The paper also discusses the current challenges, scope for improvement, and the future trajectory of traffic modeling to enable smarter, adaptive traffic management systems. These developments not only improve real-time decision-making but also provide valuable insights for long-term transportation planning.
Keywords: Traffic Simulation, Congestion Prediction, Urban Mobility, Traffic Flow Modeling, Intelligent Transport Systems
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