Traffic Congestion Prediction Using Machine Learning Techniques
Machine Learning
2025-04-22 v5 Signal Processing
Abstract
The prediction of traffic congestion can serve a crucial role in making future decisions. Although many studies have been conducted regarding congestion, most of these could not cover all the important factors (e.g., weather conditions). We proposed a prediction model for traffic congestion that can predict congestion based on day, time and several weather data (e.g., temperature, humidity). To evaluate our model, it has been tested against the traffic data of New Delhi. With this model, congestion of a road can be predicted one week ahead with an average RMSE of 1.12. Therefore, this model can be used to take preventive measure beforehand.
Cite
@article{arxiv.2206.10983,
title = {Traffic Congestion Prediction Using Machine Learning Techniques},
author = {Rafed Muhammad Yasir and Moumita Asad and Naushin Nower and Mohammad Shoyaib},
journal= {arXiv preprint arXiv:2206.10983},
year = {2025}
}
Comments
This is an undergraduate research project and it isn't sufficiently exhaustive