People
doc. Ing. Michal Matowicki, Ph.D.

Mgr. Miloslav Kučera

PLIADES advances the SoA dataspaces reference architectures, towards a step change on the use of data as key enabler of technological advances in AI and Robotics. To this end, PLIADES researches into novel, AI-enabled tools to advance full data life cycles integration, both within and between data spaces. Sustainable data creation methods through data compression, filtering and normalization will be developed, to allow efficient and greener storage in a data-oriented future. Data privacy and sovereignty will be further ensured, through standards and decentralized protocols to protect data-producing organizations and citizens. Alongside, data sharing will be revolutionized through novel AI-based brokers and connectors using extended metadata, shaped through the project’s best practices and domain expert’s knowledge. On top of these, active data discovery services through cross domain AI connectors will allow creating linked data spaces, enabling interoperability between previously disconnected entities, while data quality assessment services will facilitate real time data evaluation. Extended synergies with EU initiatives will be established in order to contribute models, strategies and technologies for a Common European Data Space. Our outcomes will be evaluated in six use cases focusing on direct advancements in key AI and Robotics technologies for everyday use, oriented around multiple data spaces; mobility, healthcare, industrial, energy and green deal. Our use cases provide a challenging validation suite involving vast heterogeneous data creation, management and sharing while addressing full data lifecycles in multiple major domains. Through the developed ecosystem, CCAM and ADAS/AD car technologies will be enhanced, HRI for robot operators and healthcare patients will be reshaped, while further advanced, integrated data spaces will be deployed in the healthcare, manufacturing and green deal sectors aiming to reduce carbon footprints and shape a greener future.

2024 - 2027

Horizon Europe - 101135988

Ing. Bc. Petr Kumpošt, Ph.D.; doc. Ing. Michal Matowicki, Ph.D.; prof. Ing. Ondřej Přibyl, Ph.D.; Ing. Dan Ťok

The project aims at future effective reduction of individual transport, which often emerges where it is inefficient for PT companies to create PT lines. This can be realized through the deployment of automated minibuses (AM) in the form of MoD. The need for their efficient management and supervision is obvious then, thus semi-automated control center to ensure efficient and safe operation of AMs is the main goal of the project. Such center will focus on dynamic routing of AM lines, identification of incidents in the vehicle and methods for teleoperation, which are specifically necessary for the safe and reliable operation of AM both from the point of view of passengers and from the point of view of operation in the road traffic system.

Department of Security Technologies and Engineering

2023 - 2025

TREND

Ing. Bohumil Kovář, Ph.D.; Ing. André Maia Pereira, Ph.D.; doc. Ing. Michal Matowicki, Ph.D.

[preliminary by Google Translate] The project will create a set of components and verify in practice the functioning of a simulation-modeling framework for in-depth analysis of the behavior of intelligent transport systems in cities in real time and for research into urban traffic management strategies with emphasis on cooperative systems. The proposed intelligent transport system will be able to receive data from available sensors (traffic detectors, cameras, cooperative vehicles, pedestrians, other IoT elements of the transport system), consolidate this data into a single structure so that it can be used as input values of traffic simulation. The simulation will run on real-time data and will reflect the current situation in the modeled area. It will therefore be possible to deploy it as an ITS system analyzing in real time the impacts of traffic management decisions. The output of the project is, among other things, the methodology of creating digital transport twins.

2021 - 2024

Program na podporu aplikovaného výzkumu, experimentálního vývoje a inovací v oblasti dopravy - DOPRAVA 2020+

Ing. Bohumil Kovář, Ph.D.; Ing. Jana Kuklová, Ph.D.; prof. Ing. Ondřej Přibyl, Ph.D.; Dr. Ing. Jan Přikryl

The goal of the VEXA project is the development of an expert system which will be able to substitute reaction and decision-making abilities of train drivers to predefined inputs. The inputs cover different sources, among others sensors monitoring obstacles or fire, or configuration and actual status of the environment. These inputs will be compared to the legislative and operational rules and based on that will provide output to other train control systems. The algorithms will also cover the psychosomatic characteristics of the train drivers. The solution will be based on a detailed system analysis, data collection, definition of interfaces, system architecture and mathematical analysis to assess its impact and operation parameters.

2020 - 2022

Program na podporu aplikovaného výzkumu, experimentálního vývoje a inovací v oblasti dopravy - DOPRAVA 2020+

Ing. Jana Kuklová, Ph.D.; prof. Ing. Ondřej Přibyl, Ph.D.

In days of increasing popularization of intelligent transport systems and Smart City solutions, traffic management systems become increasingly common. One of their applications are traffic information systems, which inform drivers about traffic conditions ahead by means of variable message signs. The goal of the proposed project is understanding of drivers subjective evaluation of traffic conditions. With help of experiment, we will record driving of equipped vehicle in various conditions, and later construct a questionnaire that will ask various drivers to evaluate conditions visible on each short record. Such evaluations will let us a insight view to subjective traffic conditions perception by various drivers, and analysis of traffic stream parameters like speed and density to determine which of them influence drivers evaluation.

2019 - 2020

Studentská grantová soutěž ČVUT - SGS19/120/OHK2/2T/16

Ing. Jana Kuklová, Ph.D.; prof. Ing. Ondřej Přibyl, Ph.D.; Ing. Dmitrij Rožděstvenský, Ph.D.

This project focuses on detailed study of tolerance and compliance of the drivers to VSL systems. An eye tracking device will be used to track reaction of the drivers to changes in Variable Speed Limits and their compliance to the imposed speed limits. Detailed analysis of the data will allow to establish the level of drivers tolerance for VSL systems. Preliminary studies on data from detectors on Prague city rings shows interesting results that can be used for design of a next generation Highway Management Systems . This project aims to deliver the detailed insight into why and how exactly drivers react to different speed limits.

2016 - 2017

Studentská grantová soutěž ČVUT - SGS16/186/OHK2/2T/16

doc. Ing. Michal Matowicki, Ph.D.; prof. Ing. Ondřej Přibyl, Ph.D.

New algorithms for traffic control on Czech highways and freeways will be developed in this project, considering the main focus on advanced control approaches (fuzzy logic, multi-agent systems, genetic algorithms, neural networks etc.). The algorithms tested and introduced abroad will be studied. Afterwards, their transferability to the Czech conditions will be discussed. The newly developed algorithms will be compared with the algorithm currently used on Czech highways. The algorithms' testing and their comparison will be performed using the microsimualtion software Aimsun.

2015 - 2016

Studentská grantová soutěž ČVUT - SGS15/169/OHK2/2T/16