Enriched Traffic Datasets for Madrid

DESCRIPTION OF THE RESEARCH AND DATA:
This work presents the Madrid Traffic Dataset (MTD), a comprehensive resource for the analysis and modeling of traffic patterns in Madrid. The dataset integrates data from traffic sensors, weather observations, calendar information, road infrastructure, and geolocation data to support advanced studies of urban mobility and predictive modeling.

In addition to the core data sources, the dataset includes temporal sequences and a traffic adjacency matrix, enabling the application of time-series analysis and graph-based modeling approaches.

-COMPLETE DATASET:
The complete version of the MTD includes data from 554 traffic sensors distributed across the Madrid region, covering a total of 30 months (from June 2022 to November 2024).

-SUBSET DATASET:
A more compact version derived from the complete dataset, focused on a subset of 300 traffic sensors with 17 months of data (from June 2022 to October 2023). This subset is designed for researchers requiring a lighter dataset.

DATA ORGANIZATION:
The dataset is organized in a main directory containing a subfolder identified by the configuration data hash. This subfolder includes all key components: datasets, temporal sequences, adjacency matrices, and configuration files. The structure ensures that all resources are clearly arranged to facilitate easy access and reproducibility for researchers.

For more details, see the associated article: Gómez, I. and Ilarri, S., Advanced Prediction of Traffic at Different Temporal Scales Using Heterogeneous Data Sources, IEEE Open Journal of Intelligent Transportation Systems, 2025. DOI: 10.1109/OJITS.2025.3637305.