AI-Powered Urban Mobility Analysis for Advanced Traffic Flow Forecasting

Sarah Di Grande, Mariaelena Berlotti, Salvatore Cavalieri

2024

Abstract

Rapid global urbanization has resulted in burgeoning metropolitan populations, posing significant challenges for managing transportation infrastructure. Despite various attempts to address these issues, persistent challenges hinder urban growth. This study emphasizes the crucial need for effective traffic flow forecasting in city traffic management systems, with Catania serving as a case study due to its notable traffic congestion. Predicting traffic flow encounters obstacles, such as the cost and feasibility of deploying sensors across all roads. To overcome this, the authors suggest an innovative two-level machine learning approach, involving an unsupervised clustering model to extract patterns from extensive sensor-generated big data, followed by supervised machine learning models forecasting traffic within individual clusters. Notably, this method allows predictions for roads without sensor data by leveraging a small subset of alternative data sources.

Paper Citation

in Harvard Style

Di Grande S., Berlotti M. and Cavalieri S. (2024). AI-Powered Urban Mobility Analysis for Advanced Traffic Flow Forecasting. In Proceedings of the 13th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS; ISBN 978-989-758-702-3, SciTePress, pages 57-64. DOI: 10.5220/0012625900003714

in Bibtex Style

@conference{smartgreens24,
author={Sarah Di Grande and Mariaelena Berlotti and Salvatore Cavalieri},
title={AI-Powered Urban Mobility Analysis for Advanced Traffic Flow Forecasting},
booktitle={Proceedings of the 13th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS},
year={2024},
pages={57-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012625900003714},
isbn={978-989-758-702-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS
TI - AI-Powered Urban Mobility Analysis for Advanced Traffic Flow Forecasting
SN - 978-989-758-702-3
AU - Di Grande S.
AU - Berlotti M.
AU - Cavalieri S.
PY - 2024
SP - 57
EP - 64
DO - 10.5220/0012625900003714
PB - SciTePress