General information

Project #:	517374-TEMPUS-1-2011-1-RU-TEMPUS-JPCR
Project:	Communication and Information Technology for Improvement Safety and Efficiency of Traffic Flows: EU-RU-UA Master and PhD Programs in Intelligent Transport Systems
Project acronym:	CITISET
Project duration:	15.10.2011 – 31.12.2018
EU funding instrument:	Regional Program European Neighborhood and Partnership Instrument
Tempus grant amount:	ˆ 1 127 487,50
Target group:	Students, teachers, university administration staff; enterprises, organizations and graduates employ institutions
Grant holder and Coordinator:	Saint-Petersburg state university of aerospace instrumentation
Contacts:	Director of the International Institute for Advanced Aerospace Technologies (IIAAT) of SUAI Prof. Alexander Nebylov tel.: +7 812 494-70-16 e-mail: Head of International Department of SUAI Julia Makarova tel.: +7 812 312-09-37 e-mail:

Project goals and objectives

Safety and effectiveness increasing of Air, Sea, Railway and Road vehicles motion flows, including negative influence decrease on environment, by profile universities cooperation from Ukraine, the Russian Federation and EU countries towards expert training on the specialty "Intelligent Transport Systems" (ITS), which are based on modern ICT implantation in motion control of transport vehicles and systems.

Harmonization and co-ordination by Russian and Ukrainian universities, participants of the Project, Master and PhD Programs in knowledge area "Transport and Transport Infrastructure" with corresponding EU Master and PhD Programs and giving to students from four Russian and four Ukrainian universities the possibility of study from September 2015 on the new "ITS" Master/PhD Program as in home, so in foreign university, which participates in the Project.

Realization of activities, aimed on support and ensuring of students training in Russian and Ukrainian Universities according to EU Standards and Bologna process requirements:

• increasing of the qualification level of teachers from partner country universities;
• methodological and technical support of the ITS students’ training;
• introduction of quality assurance system of specialists training which are based on EU counties experience;
• realization students’ and teachers’ mobility including virtual mobility.

Activities

• Review of existent study programs of EU Universities in ITS on Master and PhD level and their contrastive analysis with the same level programs of PC Universities.
• Development of Joint “ITS” Master and PhD Programs.
• Increasing of RU and UA teachers’ qualification, including their training in EU Universities and also improvement of educational process methodic base.
• Creation of special laboratories for students training in the “ITS” specialty.
• Introduction of quality assurance system of educational process, which will be based on the EU Universities experience.
• Pilot students’ training.
• Project quality control and monitoring, dissemination, sustainability, management.

Expected results

• Master and PhD Programs in “ITS” are introduced in PC Universities.
• Teachers’ qualification from PC Universities is raised, including at the base of EU Universities.
• Educational and methodical materials for Master and PhD Programs are published.
• “ITS” laboratories in PC Universities and “ITS” Joint Electronic Library are created.
• Quality assurance system of student training in specialty “ITS”, which will be based on EU Universities experience is introduced.
• Specialists within new “ITS” Master Program are trained.
• Project results between different profile Universities from Russian Federation and Ukraine are disseminated.

Partnership

• Saint Petersburg State University of Aerospace Instrumentation (RU)
• Murmansk State Technical University (RU)
• Moscow State University of Railway Engineering (RU)
• Samara State Technical University (RU)
• Public Corporation "Russian Institute of Radionavigation and Time" (RU)
• National Aerospace University "Kharkiv Aviation Institute" (UA)
• Odessa National Maritime University (UA)
• Dnipropetrovsk National University of Railway Transport (UA)
• Zhytomyr State Technological University (UA)
• Linkoping University (Sweden)
• University of Southampton (Great Britain)
• Transport and Telecommunication Institute (Latvia)
• Silesian University of Technology (Poland)

Within the framework of the project, four types of transport vehicles with intellectual support have been addressed for: air, road, rail and sea. Respectively, all participants are grouped according to the specified mode of transport. In the group of air transport are included Saint-Petersburg State University of Aerospace Instrumentation (SUAI), National Aerospace University "Kharkiv Aviation Institute" (KhAI), and University of Southampton.

By agreement among these universities, implementation of the vision "Intelligent Aircraft” (IA) will be made in the curriculum for Master and PhD students.

The concept of Intelligent Aircraft

In today’s world, great emphasis is placed on safety and efficiency of air transportation. These demands have led to an astounding pace of development in avionics and airborne navigation. Computer processing, electronic charts, and radio navigation techniques, in particular the Global Positioning Systems, will provide precise navigation available to every pilot. Intelligent air navigation systems range from small satellite navigators, to complex motion control systems that integrate many navigation and positioning systems with aeronautical charts and other information systems on the aircraft.

The concept of IA based on the methods of artificial intelligence are applied to on-board aviation complex which functions under prevailing uncertainty and are actually intended to provide a comfortable and efficient operation of the pilot or crew.

One of the key trends in the way of a future IA is the development of foundations of construction board of control systems and decision support. In the modern terminology, it is a system that actively uses the knowledge and experience of experts, focused on early intervention in the work of the controlled plant (i.e. the IA and its subsystems) based on analysis of continuously changing pattern of external and internal environment. Otherwise, they are called onboard operational expert decision-making/support systems, real-time expert systems or active expert systems. In turn, these systems belong to a class of systems based on knowledge (knowledge-based systems), or intelligent systems. Intelligent Control System (ICS) is one in which knowledge about the unknown characteristics of the controlled vehicle and the environment are formed in the process of learning and adaptation, and thus the resulting information is used in the process of automated decision-making so that the quality of control improves.

Intelligent control systems are systems organized and operating in accordance with the following principles:

1. Interaction with the real external world with the use of information channels.
2. The principle of openness in order to increase intelligence and improve the behavior of controlled vehicle.
3. The presence of mechanisms to predict changes in the external world and own behavior of the system.
4. The presence of multi-level hierarchical structure constructed in accordance with the rule: increasing intelligence and reducing demands on the accuracy of models with increasing levels of hierarchy in the system (and vice versa).

Control algorithms of this level ones can be represented as:

• systems with adaptation, which provides a mechanism for adjusting the algorithms of control actions when the conditions of flight are changed;
• robust system in which the structure of control algorithms are predefined.

In recent years, to solve the above-mentioned problems are being increasingly used the methods of the theory of Neural Networks (NN). NN is referred as the parallel computing structures that model the processes, usually associated with processes of the human brain. NN have the ability to acquire knowledge about the subject area under study, learning from examples. Among the indisputable advantages of NN, while explaining the increased interests to them by the experts are:

• Capability of reproduction the difficult non-linear dependences;
• NN do not demand complex programming;
• Fast response time (especially in case of a hardware representation with the use of parallel handling);
• Potentially high noise proof and fail-safety;
• Universality of application, a capability of the solution of badly formalizable problems (pattern and speeches recognition, the cluster analysis, identification, the prediction, etc.).

Today it is already established new types of aircraft, providing qualitative breakthrough in the development of aviation, but to achieve their potential performance it is required to use the new approaches to the construction and functioning of aircraft systems.

Modern trends in on-board control systems related to their future intellectualization, a technology-based knowledge processing to automate control functions and support the actions of the crew both in normal and in emergency situations that arise during the flight.

One promising direction in the establishment of control systems and decision-making is the use of NN and their hardware and software implementation based on the new generation of computers - neurocomputers that exceed other types of computers, not only by efficiency/cost value, but also by their ability to solve non-standard, poorly formalized problems.

Intelligent On-board systems for Crew Support

Nowadays when designing smart-board systems to support the crew, the following technologies are used: Expert Systems, Artificial Neural Networks, Fuzzy mathematics, mathematical optimization methods, heuristic algorithms, genetic algorithms, hybrid technology, based on different combinations of the above-mentioned approaches.

On-board intelligent systems, monitoring of operating condition of aircraft equipment

Intelligent monitoring of operating condition of the onboard equipment are being developed as a response to dissatisfaction of the crew with regard to incomplete information arising due to failure of onboard equipment. Currently the available systems of automatic monitoring only fix the failure. Tasks of failure estimation and its influence on continuing the success of flight, including the problem of determining the remaining operationability of on-board equipment, the problem of the influence of failure on the continuation of the current flight and the definition of a rational method of localization (removing) of failure by issuing recommendations on the reconfiguration of the control system for the crew. These recommendations must be given with the help of specialized "flexible" algorithms in a specific digital computer. Thus, the science and practice of aviation come to the stage of creating on-board intelligent systems.

The curriculum on Intelligent Transport Systems

Masters and postgraduate programs in SUAI associated with intelligent transportation systems are held in various areas of training. The training programs include the following subjects, supporting the development of the concept of ITS:

• Research and development of methods for obtaining and processing information
• Mathematical methods of information processing
• Information technology in instrument-making
• Mathematical modeling in instrument systems
• Monitoring and diagnostics of measuring and computing systems
• System Analysis
• Research and development of methods for obtaining and processing information
• Mathematical methods of information processing
• Information technology in instrument
• Mathematical modeling in instrument systems
• Monitoring and diagnostics of measuring and computing systems
• Automatic Control Systems of aircraft
• Complexes of navigation and piloting
• Intelligent tutoring systems
• Models of signal and noise instrumentation systems
• Modern information technology
• Aircraft simulator and learning systems
• On-board intelligent avionics systems
• On-board advising system
• Smart micro-mechanical sensors
• Digital control system
• Satellite-based navigation and communication

Laboratory model of warning system for critical regime of the flight

Tutorials created in the project

• Tutorial: Positioning Systems of Transport Vehicles