CODECO Mobility Datasets

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Authors: Jordi Marias-i-Parella
Cited by: 0

Abstract

CODECO — Mobility Datasets This repository holds the mobility datasets produced within the CODECO (COgnitive DECentralized Orchestration) European research project (Horizon Europe, Grant Agreement No. 101092696). All datasets in this repository correspond to Use Case 2 (UC2): Vehicular Digital Twin for Safe Urban Mobility, which focuses on improving road safety in urban environments through the use of digital twins, V2X communications, and machine learning-based risk detection. Datasets HEU-101092696-CODECO-Trajectories This dataset contains simulated trajectory records of private passenger vehicles in an urban environment specifically designed to provoke lateral and frontal collisions. Generated using the SUMO traffic simulator with the TraCI interface, the scenarios are geolocated in central Barcelona and include reckless driving behaviours such as traffic light violations and speeding. It is primarily intended for training and evaluating ML-based collision prediction and avoidance algorithms. HEU-101092696-CODECO-VRUMobility This dataset contains real-world trajectory and mobility records of Vulnerable Road Users (VRUs) — pedestrians, cyclists, and electric scooter riders — as well as motor vehicles, collected over multiple days at the UPC campus and i2CAT offices in Barcelona using camera sensors and V2X communications. The data fields are aligned with ETSI ITS VAM and CAM message standards and are intended for improving VRU risk detection algorithms and enhancing orchestration within the CODECO framework. License All datasets in this repository are released under the ODC Open Database License (ODbL). See the individual dataset README files for details. Project website: https://www.codeco-project.eu

Fields of Study & Subjects

Traffic and Road Safety Vehicular Ad Hoc Networks (VANETs) Traffic control and management

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
13 March 2026
Language
EN
Document type
Dataset