TrafficDator: TRAFFIC Data Analysis and predicTiOn for betteR mobility

Brief description

Within the NEAT-AMBIENCE project, we tackle the development of novel and suitable data management techniques to help citizens in their daily life. Particularly, with TrafficDator (TRAFFIC Data Analysis and predicTiOn for betteR mobility) our goal is to develop methodologies and strategies for predicting traffic in both the short term and long term by integrating a variety of data sources.

Software and datasets

TrafficDator — GitHub repository
Iván Gómez, Sergio Ilarri, "TrafficDatorNet: Code and Baselines for Traffic Prediction with Heterogeneous Data (Madrid Traffic Dataset)", Mendeley Data, 2025. DOI: 10.6084/m9.figshare.30391069.
Iván Gómez, Sergio Ilarri, "Enriched Traffic Datasets for Madrid", Mendeley Data, 2025. DOI: 10.17632/697HT4F65B.2.
Iván Gómez, Sergio Ilarri, "TrafficDator Madrid", Zenodo, 2024. DOI: 10.5281/ZENODO.10435153.

Main Related Publications

Iván Gómez, Sergio Ilarri, "Advanced Prediction of Traffic at Different Temporal Scales Using Heterogeneous Data Sources", IEEE Open Journal of Intelligent Transportation Systems, ISSN 2687-7813, pp. 1539-1550, IEEE, volume 6, November 2025.

(DOI: 10.1109/OJITS.2025.3637305)

Iván Gómez, Sergio Ilarri, "Enriched Traffic Datasets for the City of Madrid: Integrating Data from Traffic Sensors, the Road Infrastructure, Calendar Data and Weather Data", Data in Brief, ISSN 2352-3409, volume 57, article 110878, 13 pp., Elsevier, December 2024.

(DOI: 10.1016/j.dib.2024.110878)

Sergio Ilarri, Raquel Trillo-Lado, Lorena Marrodán, "Traffic and Pollution Modelling for Air Quality Awareness: An Experience in the City of Zaragoza", Springer Nature Computer Science, ISSN 2661-8907, volume 3, article 281, pp. 281:1-281:33, Springer, 2022. Special Issue on Web Information Systems and Technologies 2021.

(DOI: 10.1007/s42979-022-01105-0)

Main Researchers

Acknowledgments

We cite below our current funding projects:

Project PID2020-113037RB-I00 / AEI / 10.13039/501100011033 — Next-gEnerATion dAta Management to foster suitable Behaviors and the resilience of cItizens against modErN ChallEnges (NEAT-AMBIENCE)
Government of Aragon (COSMOS research group; last group reference: T64_23R)

Brief description

Software and datasets

Main Related Publications

Main Researchers

Acknowledgments

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