Projects
TRALICO: Multi-Input Deep Learning for Congestion Prediction and Traffic Light Control (TRALICO)
This solution is significant and unique as no similar solution has been tested in real life situations in a large urban environment in Europe or in Japan before. A key objective of the project is to have the partners test this solution in real life traffic conditions too, in one of the world’s largest cities, Istanbul. The reference solution created in Istanbul in the course of the three-year project is also expected to strongly support the solution’s future marketing as a large number of cities are interested in a similar solution.
Duration: 2024-2027
Source of funding: European Interest Group CONCERT-Japan programme.

Miracle: address traffic congestion while promoting sustainability through the implementation of dynamic toll pricing
Duration: 2024-
Source of funding:
CELSA: Machine Learning-Based Cooperative Vehicle and Traffic Control Using Secure ML and V2X Communications
Duration: 2023-2025
Source of funding: CELSA Research Fund (Central Europe Leuven Strategic Alliance)
Vehicle Cybersecurity
Duration: 2021, 36 months
Funding: Artificial Intelligence National Laboratory Program
Federated Learning-Driven Network and Service Management
Duration: 2022, 6 months
Source of funding: GÉANT Innovation Programme

Intelligent transportation system – Competitiveness and excellence cooperations 2018-1.3.1-VKE
Duration: 2019-2023
Source of funding: National Research, Development and Innovation Office, Hungary

C-ITS/V2X R&D projects
Duration: 2018-
Sources of funding: Magyar Közút, National Infrastructure Developing Ltd.

AWARD: Autonomous Warehouse and Last Mile Delivery
Duration: 2018-2019
Source of funding: EIT Digital