Consortium

Vilnius Gediminas Technical University (VT)

VT contribute its expertise to the MOCO consortium by providing knowledge in cutting-edge virtual sensor technologies designed for ground vehicle control systems. Researchers at VT possess a diverse skill set encompassing vehicle dynamics, state estimation and AI, allowing for a cross-disciplinary approach. Together with partners from UTC and TEN researchers will contribute to hybrid estimator development. Furthermore, VT will leverage its existing HIL system and vehicle demonstrator, tailoring them specifically for MOCO activities. The combined expertise, along with access to advanced software and hardware solutions and project partners’ know-how, will ensure the success of the MOCO project.

AGH University of Krakow (AGH)

AGH specialises in the mathematical control theory, state observation, and identification of dynamic systems. The research in the MOCO projectconcerns modern methods of controlling the state of dynamic systems based on a new type of state observers that reconstruct the exact state after any pre-defined time. These observers are built based on integral operators working on a finite time-sliding window, not on differential equations. So they work differently than the Kalman Filter, which only gives an asymptotic estimate of the state at an unknown time. Additionally, the active safety control of AVs will be investigated. The methods are based on recognising and understanding the road situation by the analysis of images from cameras.

Aragón Institute of Technology (ITA)

ITA is the Aragon Institute of Technology and its main objective is the development of technology solutions for the industry. The mechatronics group is taking part in the MoCo project. The contribution to the project is made twofold: definition of an MBSE methodology guiding the development of pilot cases, from their requirements to testing, creating new metamodels to integrate perspectives of components and simulation models; and use of differential flatness for identification and feedforward control purposes. In the last case, it will be used in combination with the other developed feedback controllers for assuring robustness.

APTIV Services Poland S.A. (APT)

APT, a leading global supplier of automotive technologies, the APTIV Technical Center Krakow, which houses a state-of-the-art Validation Laboratory, design offices, and a test track. These facilities are dedicated to researching the control of automated vehicles and active safety systems. APT will be open to partners for the development and collaborative refinement of motion control systems and sharing expertise in functional safety.

Technische Universiteit Delft (TUD)

TUD has strong expertise in the development of intelligent vehicle motion control and driving simulator technologies that will be used in the MOCO project. The research experience covers various model predictive techniques such as nonlinear model predictive control, model predictive contouring control, learning–based predictive control, model predictive control allocation for vehicle motion planning and control, concurrent vehicle subsystems control, and driver assistance/support systems. TUD will contribute to the design of predictive and optimization-based control strategies and conduct experimental investigations using a moving-based driving simulator.

French National Centre for Scientific Research (CNRS)

CNRS will input their huge aerial robot modelling and control competence in MOCO consortium to contribute to the project parts related to drone-vehicle interaction. Subjects related to robust control and stabilisation of multi-actuated vehicles and cooperative navigation of aerial and MAGV will be discussed and developed in the MOCO consortium, with support from CNRS.

Graz University of Technology (TUG)

TUG is a renowned research university specialising in control theory and engineering research and will contribute to discretising observers, implementing them in discrete-time, employing higher-order sliding-mode observers (HOSMO) for parameter estimation in automotive applications, and applying enhanced control methods such model predictive and sliding mode control.

Technische Universität Ilmenau (TUIL)

TUIL has strong expertise in the chassis and powertrain control design of EVs as well as in x-in-the-loop testing technologies for complex systems. With this competence, TUIL contributes to the MOCO project through the development of low-level (actuator-level) elements of the motion control systems, and experimental validation of the developed controllers using XIL environments and vehicle demonstrators. Moreover, TUIL will provide training both for the seconded staff and the consortium-wide in these topics.

Tenneco Automotive BV (TEN)

TEN is a world-leading TIER 1 in chassis systems and components and will provide the MOCO consortium with deep competence in the development, design and production of vehicle chassis components and estimators for their control. TEN will support the project with the testing of jointly developed solutions using their facilities, which will be developed and tested in collaboration with other partners. A valuable contribution of TEN consists of training staff from academic participants of the consortium in advanced chassis design.

University of Technology of Compiegne (UTC)

UTC will contribute to MOCO by integrating his expertise in embedded computer systems and experimental developments, applied to dynamic state estimation, control and autonomous navigation of MAGV. A specificity that will benefit MOCO partners concerns the UTC developments and competencies on human-machine interactions by virtual or augmented reality tools. Finally, the developments on vehicle autonomous navigation awareness to the semantic context will be a matter of exchange on the MOCO consortium.

University of Tokyo (UT)

UT will train incoming staff from the European participants of the consortium in modern control engineering technologies with a particular focus given to electric vehicle mechatronic systems. For this purpose, several UT vehicle demonstrators will be used. UT will also support other partners involved in the development of vehicle motion controllers.

Korea Automotive Technology Research Institute (KAT)

KAT is a prestigious research organisation focusing on science, engineering, and technology. It has a strong reputation for its research contributions, innovative programs, and collaborations with industry partners. KAT has an independent proving ground to test and validate the performance of the AV, which will be available for project partners during the MOCO project. Incoming staff from the EU will be trained in the field of testing technologies using modern techniques.

National Autonomous University of Mexico (UNAM)

UNAM is a prestigious institution known for its academic excellence and excellent expertise in sliding mode theory. It will design HOSMO for uncertain mechanical systems, extend to networked systems, develop continuous higher-order sliding-mode controller and integrate them with HOSM observers. Collaborating with the MOCO partners, UNAM will develop adaptive observers and parameter estimation algorithms.

University of Pretoria (UP)

UP is a premier research institute specialising in off-road vehicle dynamics, specifically emphasizing tire-terrain modelling and vehicle dynamics control in unstructured/uncertain environments. Aligned with these focal points, UP has extensive proficiency in multi-body dynamics modelling and experimental validation, especially on rough and off-road terrain. Having collaborated on two prior MSCA-RISE projects, namely EVE and OWHEEL, UP has actively contributed to vehicle modelling, experimental validation, and ride comfort assessment in these initiatives.