Road Traffic Forecasting using AirPollution and Atmospheric Data

Author(s)	Nithya P, Sivamurugan S, Vedapriya N, Vijayashree K
Country	India
Abstract	In this paper, we propose a novel machine learning approach integrating environmental data into road traffic forecasting models. By leveraging historical data on road traffic, air pollution, and atmospheric parameters, we develop predictive models capable of capturing the intricate interplay between traffic patterns and environmental conditions. Our experimental results demonstrate the effectiveness of our approach in improving traffic forecast accuracy compared to conventional methods. This research contributes to advancing understanding of how environmental factors impact traffic dynamics, offering practical insights for enhancing urban transportation management strategies.
Keywords	Machine Learning , Air Pollutant , Pollution , Traffic , Traffic pollution , Atmospheric data , Accuracy , Human Health , Sustainable Environment
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-05-16
Cite This	Road Traffic Forecasting using AirPollution and Atmospheric Data - Nithya P, Sivamurugan S, Vedapriya N, Vijayashree K - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20402
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.20402
Short DOI	https://doi.org/gtvtzz

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