Evaluation of Level 2 Automated Driving Artificial Intelligence Readiness in Simulated Scenarios. - David Tena-Gago; Qi Wang 001; José M. Alcaraz-Calero (CSCS, 2022)

Transfer Learning-Enabled IoT System for Continuous Prediction of Vehicle CO2 Concentration. - Mohammad Alselek; David Tena-Gago; José M. Alcaraz-Calero; Qi Wang 001 (ISC2, 2023)

Machine-Learning-Based Carbon Dioxide Concentration Prediction for Hybrid Vehicles. - David Tena-Gago; Gelayol Golcarenarenji; Ignacio Martinez-Alpiste; Qi Wang 001; José M. Alcaraz-Calero (Sensors, 2023)

Non-invasive, plug-and-play pollution detector for vehicle on-board instantaneous CO2 emission monitoring. - David Tena-Gago; Qi Wang 001; José M. Alcaraz-Calero (Internet Things, 2023)

Optimizing AI Transformer Models for CO₂ Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support. - Javier Sáez-Pérez; Pablo Benlloch-Caballero; David Tena-Gago; José García Rodríguez 001; José Maria Alcaraz Calero; Qi Wang 001 (IEEE Access, 2024)

Design, Implementation and Validation of a Level 2 Automated Driving Vehicle Reference Architecture. - Javier Sáez-Pérez; Julio Diez-Tomillo; David Tena-Gago; José M. Alcaraz Calero; Qi Wang 001 (Expert Syst. J. Knowl. Eng., 2025)