machine learning - DSAIT NTUA

Projects

Enhanced Data Processing Techniques For Dynamic Management Of Multimodal Traffic

Shared Automation Operating Models for Worldwide Adoption

Publications

From Travel Times to Lane-Based Hourly Traffic Flow: An Explainable Machine Learning Framework

Charis Chalkiadakis & Eleni I. Vlahogianni

Data Science for Transportation 7, 18, 2025

Revisiting the Non-recurrent Traffic Incident Identification Problem for Real-Time Applications Using Theory-Aware Unsupervised Learning

Papadatou, K. Ν., Fafoutellis, P., & Vlahogianni, E. I.

Data Science for Transportation, 7(2), 12, 2025

Mixed traffic microscopic interactions modelling in shared space using machine learning

E Mantouka, E Kampitakis, P Fafoutellis, E Vlahogianni

Advances in Transportation Studies 65, 2025

Leveraging multisource data for οff-street parking occupancy prediction: A twofold analysis

K Vakrinou, EG Mantouka, EI Vlahogianni

International Journal of Transportation Science and Technology, 2025

Traffic demand prediction using a social multiplex networks representation on a multimodal and multisource dataset

P Fafoutellis, EI Vlahogianni

International Journal of Transportation Science and Technology 14, 171-185, 2024

Reconstructing mobility from smartphone data: Empirical evidence of the effects of COVID-19 pandemic crisis on working and leisure

V Mourtakos, EG Mantouka, P Fafoutellis, EI Vlahogianni, K Kepaptsoglou

Transport Policy 146, 241-254, 2024

Effects of Driving Behavior on Fuel Consumption with Explainable Gradient Boosting Decision Trees

Konstantinou, C., Fafoutellis, P., Mantouka, E. G., Chalkiadakis, C., Fortsakis, P., & Vlahogianni, E. I.

8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE, 2023

Empirical investigation of shared space traffic: A comparison to conventional urban road environment

PG Tzouras, K Kepaptsoglou, EI Vlahogianni

International Journal of Transportation Science and Technology 15, 122-135, 2023

Investigating the impacts of the COVID-19 pandemic on Eco-driving behaviors

Fafoutellis, P., Mantouka, E. G., Vlahogianni, E. I., & Fortsakis, P.

Safety Science, 166, 106251, 2023

Acceptability modeling of autonomous mobility on-demand services with on-board ride sharing using interpretable Machine Learning

Fafoutellis, P., Mantouka, E. G., Vlahogianni, E. I., & Oprea, G. M.

International Journal of Transportation Science and Technology11(4), 752-766, 2022

Smartphone sensing for understanding driving behavior: Current practice and challenges

Mantouka E., Barmpounakis E., Vlahogianni E. & Golias J

International Journal of Transportation Science and Technology10(3), 266-282, 2021

Temporal analysis of driving efficiency using smartphone data

DI Tselentis, EI Vlahogianni, G Yannis

Accident Analysis & Prevention 154, 106081, 2021

Eco-driving and its impacts on fuel efficiency: An overview of technologies and data-driven methods

P Fafoutellis, EG Mantouka, EI Vlahogianni

Sustainability 13 (1), 226, 2020

Identifying driving safety profiles from smartphone data using unsupervised learning

EG Mantouka, EN Barmpounakis, EI Vlahogianni

Safety Science 119, 84-90

Driving analytics using smartphones: Algorithms, comparisons and challenges

EI Vlahogianni, EN Barmpounakis

Transportation Research Part C: Emerging Technologies 79, 196-206

PHD Theses

Integrating the Concept of Generic Resilience in Urban Road Networks Traffic Management

Charis Chalkiadakis

2025

Cooperative Decision Making Models for Urban Road Networks

Marios Giouroukelis

2021

#machine learning