The Role of Big Data Analytics in Predicting and Managing Urban Traffic Flow

Author(s)	Rashi Nimesh Kumar Dhenia
Country	India
Abstract	As urban populations and vehicle numbers surge, cities worldwide face mounting challenges related to traffic congestion, pollution, and transportation inefficiency. Traditional traffic management techniques are increasingly inadequate for these complexities. Big data analytics—leveraging vast, heterogeneous data sources and advanced machine learning—has emerged as a transformative approach for predicting, analyzing, and managing urban traffic flow. This paper provides a comprehensive review of the application of big data analytics in urban traffic management, exploring data sources, predictive methodologies, real-time systems, case studies, challenges, and future prospects. Supported by recent literature and real-world implementations, this discussion demonstrates how data science is shaping the evolution of intelligent transportation systems and smarter, more sustainable cities.
Keywords	Big Data Analytics, Urban Traffic, Real-Time Prediction, Machine Learning, Smart Cities.
Field	Engineering
Published In	Volume 3, Issue 2, March-April 2021
Published On	2021-03-16
DOI	https://doi.org/10.36948/ijfmr.2021.v03i02.52045

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International Journal For Multidisciplinary Research