Predicting Urban Traffic Congestion with VANET Data

The purpose of this study lies in developing a comparison of neural network-based models for vehicular congestion prediction, with the aim of improving urban mobility and mitigating the negative effects associated with traffic, such as accidents and congestion. This research focuses on evaluating th...

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Bibliographic Details
Published in:Computation
Main Authors: Wilson Chango, Pamela Buñay, Juan Erazo, Pedro Aguilar, Jaime Sayago, Angel Flores, Geovanny Silva
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Subjects:
congestion prediction
neural networks
urban mobility
machine learning
traffic management
Online Access:https://www.mdpi.com/2079-3197/13/4/92

Internet

https://www.mdpi.com/2079-3197/13/4/92

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