Bus Ridership Prediction and Scenario Analysis through ML and Multi-Agent Simulations

Bus Ridership Prediction and Scenario Analysis through ML and Multi-Agent Simulations

This paper introduces an innovative approach to predicting bus ridership andanalysing transportation scenarios through a fusion of machine learning (ML) techniques and multi-agent simulations. Utilising a comprehensive dataset from an urban bus system, we employ ML models to accurately forecast pass...

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Bibliographic Details
Main Authors: Pasqual Martí, Alejandro Ibáñez, Vicente Julian, Paulo Novais, Jaume Jordán
Format: Article
Language:English
Published: Ediciones Universidad de Salamanca 2024-12-01
Series:Advances in Distributed Computing and Artificial Intelligence Journal
Subjects:
passenger prediction
urban mobility
agent simulation
Online Access:https://revistas.usal.es/cinco/index.php/2255-2863/article/view/31866
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