International Transportation (69) 1 | 2017 38 The intelligent railway system theory The European railway research perspective and the development of the European digital railway strategy Digital age, railway, ICT, roadmap, intelligent transport system (ITS) Digitalisation of the railway industry and its future challenges were among the main topics at the 2016 International Trade Fair for Transport Technology (InnoTrans). Digitalisation presents a new opportunity for the future of the railway industry. The digital age and the digital development of transportation also contribute to the competitiveness of the European rail industry. In Hungary, we have been conducting scientific research with the purpose of developing an intelligent railway system within the intelligent transport system since 2014. In 2017, the consortium partners will launch a research and development project worth over EUR 9.5 million. The primary goal is to build an economical branch line railway system that benefits from the advantages of IP-based technologies and artificial intelligence. Dániel Tokody, Francesco Flammini D igitalisation technology has created new opportunities for the future of the rail industry and railway networks. In particular, the development of digital transportation has contributed to the competitiveness of the European rail industry. Funds that have been allocated for the development of railway systems can be more efficiently used by generating positive effects in several different sectors, such as the rail vehicle industry or signalling and interlocking technology (cross-fertilisation). Profitability goes hand in hand with the development level of the infrastructure, including that for railway infrastructure and related services. As for the latter, poor service quality in railway transport represents one of the barriers to economic growth. In addition, safety considerations have become even more significant. Different stakeholders in the railway industry can greatly contribute to the future of the European railway and the development of a more sustainable transport system. Significant research work has been done in the field of railways in order to achieve the goals of intelligent transportation. Innovation programmes in Europe: Trends in technology In Europe the creation of a digital ecosystem is very important, especially with respect to sustainability. Digital technologies will change all aspects of transportation, including the structure of the railway system. The full digitalisation of the transportation sector will also have an effect on the quality of life, security, energy efficiency, and competitiveness. In some countries, full digital modernisation of railway systems is planned to be implemented by 2060. A full-spectrum reform of railway systems, which is necessary to develop intelligent transportation systems, still needs to be carried out. Some positive examples in Photo: Peter-Freitag/ pixelio SCIENCE & RESEARCH Digitalisation REVIEWED ARTICLE Received: 29 Mar 2017 Accepted: 21 Apr 2017 International Transportation (69) 1 | 2017 39 Digitalisation SCIENCE & RESEARCH this direction, however, reflect how railway-related research and development can be initiated by the manufacturers of rail supplies, system integrators, passenger and freight rail operators, infrastructure managers, national or international railway organisations, and university research institutes. According to a recent report published by the Association of the European Rail Industry (UNIFE), the average yearly market volume of the global railway industry is currently around EUR 160 billion. The railway sector has great innovation potential. This is reflected by the fact that in the EU, about EUR 950 million will be spent on railway research and development between 2014 and 2020 [1]. Examples of future developments in Europe include automatic obstacle-detection systems for railway vehicles, medium frequency traction transformers, energy storage technologies, improved regenerative braking, track-friendly, low-cost and silent bogies for freight wagons, complex monitoring systems, satellitebased positioning systems, hybrid and diesel electric technologies, lightweight materials, environmentallyfriendly vehicle welding procedures, the application of RFID technology, and smart railway technologies [2, 3]. Other researchand innovation-related activities that pertain to the railway industry are also being carried out, for example, in the field of advanced management and control systems. The seven main areas of such activities include smart and fail-safe communications and positioning systems, traffic management solutions, automation, moving block and train integrity, smart procurement and testing, virtual coupling, and cyber security [4]. A concrete example of research and innovation activity in these seven primary areas is the “Cybersecurity in the RAILway Sector” project (a Shift2Rail sub-project). Coordinated by Claudio Monti (from Ansaldo STS), it has a budget of EUR 1,498,150 [5]. Similarly, another subproject called “Smart Automation of Rail Transport”, under the management of Dr. Miroslav Obrenovic (Deutsche Bahn), has a budget of EUR 999,600 [6]. Unfortunately, the developments pursued in these projects represent only individual cases. As such, they are not part of a structured development strategy. Research, development, and innovation activities should be governed by scientific and business requirements and conducted proactively at independent sectoral research bases. An example of a project of this kind is the “Intelligent Railway System” project 1 with a planned budget of EUR 9.5 million. Research on and development of an intelligent and competitive railway system The purpose of intelligent systems is to make the human environment more “people-friendly”. With respect to infrastructural systems, this means that they should be sustainable, safe, economic, and easy-to-use. At the present, agent planning - the term “agent” standing for something that perceives and acts [7] - is a new field of research which aims to build intelligent systems. Intelligent railway research focuses on two areas, namely, railway system analysis and the explicit adaptation of knowledge obtained in related academic disciplines. In order to develop a model that may best grasp and describe the railway system on a theoretical-conceptual level, we are creating ontologies for artificial intelligence, knowledge management, and database management. These ontologies are being developed to ensure the provision of effectively distributed knowledge in a new structure of the railway system: We are creating a consistent knowledge base by asking various questions and answering them. We are also building and planning committed agents (i.e., anything that perceives its environment and responds or interacts to it via sensors and effectors, respectively [7]) which can safely rely on the above-mentioned ontologies. With the help of these ontologies, knowledge can be shared with the agents and among the agents. Furthermore, we are examining the safety of critical railway infrastructures by looking at different relationships with respect to security. In this process, it is also necessary to adapt knowledge generated by associated academic disciplines (e.g., general system theory, information theory, artificial intelligence, semantic systems, etc.). In this regard, Tzafestas et al. states: “The field of intelligent systems is actually a new interdisciplinary field which is the outcome of the interaction, cooperation and synergetic merging of classical fields such as system theory, control theory, artificial intelligence, information theory, operational research, soft computing, communications, linguistic theory, and others.” [8, p. 21] A new type of system, such as an intelligent system, may be understood, created, or developed further by applying the basic principles of general system theory. Here it is useful to refer to the works of biologist Ludwig von Bertalanffy and economist Kenneth E. Boulding, who made significant contributions to the foundations of general system theory. Both examined various systems from an economist’s point of view, for example, the partwhole relationships of different systems as well as the various processes within them and their self-organising mechanisms. In his hierarchical classification of systems, Figure 1. Boulding’s classification of systems, adapted to include smart and intelligent systems, as described in Tokody’s theory of intelligent systems [9, 10]. International Transportation (69) 1 | 2017 40 SCIENCE & RESEARCH Digitalisation Boulding defined nine levels of systems, ranging from simple to complex, as illustrated in figure 1 [9]. In our opinion, the level of development for currently existing railway systems corresponds to Boulding’s category of “thermostats”, which are essentially self-regulating control mechanisms or cybernetic systems that operate to maintain a pre-determined equilibrium. The important contributions of Bertalanffy and Boulding towards advancing the understanding of systems should be considered in the process of analysis. As well, theoretical advances in the field of artifical intelligence (AI), which aims to understand and create intelligent entities [11], can be applied to develop future railway systems. The “Intelligent Railway System” is based on such intelligent entities. Conclusion The lack of a long-term development strategy can negatively affect the competitiveness of the railway sector. On the other hand, on a European level, there are important developments in the railway industry. The “digitisation of everything” megatrend has an effect on the railway sector, too. Intelligent, autonomous systems must also be developed in this sector in order to ensure sustainability and safety. By using such intelligent systems, the railway infrastructure could be greatly modernised with “more trains, better connections, greater reliability.” [12, p.12] There are further opportunities for development in the railway sector. For example, cross-industry collaboration could also help to boost the economy on a European level, which is beneficial from the aspect of economic sustainability [13]. With regard to the railway sector, digitalisation involves the widespread application of digital technologies. Research and development strategies have aimed to improve and expand the European Train Control System, for example, by installing electronic interlocking equipment, increasing energy efficiency and railway safety, and implementing intelligent maintenance systems [14]. According to the European Union Agency for Network and Information Security (ENISA), smart infrastructure could be developed by combining IoT technologies with critical infrastructures, such as the railway. Public transport, including railway infrastructure, represents one part of smart infrastructures. The public transport system also is part of a larger system (i.e., the smart city), which aims to improve the quality of life for city dwellers by using information and communication technologies (ICTs) [15]. The connection of cyber and physical worlds is creating further challenges for our society. One such issue is the application of cloud-based computing. Although digital technologies like these may offer solutions for more efficient resource and documentation management, railway systems must have access to a protected and secure cyberspace. In the future, the safe operation and security of various infrastructure networks (e.g. digital railway infrastructure) will not be restricted to the “physical world” only. In summary, if the European railway sector is to remain competitive, then more research and development is needed to generate innovations that will maximize the impact of future transport systems in terms of supported economic growth, sustainability, efficiency and modal shift from road to rail [16]. The long-term development of the railway sector cannot be ensured without the use of digital technologies. Therefore, a uniform European digital railway strategy, that aims to address many of the above-mentioned points should be formulated. ■ 1 This is a new project to start 28 August 2017 in Hungary. See also: Papp, J. (2016). Embedded Control System with Shared Logic for Railroad Transport. Innorail magazine, Special Edition for InnoTrans 2016, 40-41. Retrieved from http: / / innorail.hu/ wp-content/ uploads/ 2016/ 09/ 1473093522-5c5abab- 12645dea0f8e312b0482f81da.pdf REFERENCES  [1] Ronald Berger. (2017). World rail market study forecast 2016 to 2021. Retrieved from http: / / www.unife.org/ component/ attachments/ ? task=download&id=731  [2] Flammini, F., Pragliola, C., & Smarra, G. (2016). Railway infrastructure monitoring by drones. Paper presented at the International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC), Toulouse, France. doi: 10.1109/ ESARS-ITEC.2016.7841398  [3] Tokody, D., Schuster, G., & Papp, J. (2015). Study of how to implement an intelligent railway system in Hungary. Paper presented at the IEEE 13th International Symposium on Intelligent Systems and Informatics (SISY), Subotica, Serbia. doi: 10.1109/ SISY.2015.7325379  [4] European Commission (Shift2Rail founding members). (2014). Shift2Rail strategic master plan. Brussels, Belgium. Retrieved from http: / / ec.europa.eu/ transport/ sites/ transport/ files/ modes/ rail/ doc/ 2014-09-24-draft-shift2rail-master-plan.pdf  [5] Shift2Rail. (2016). Cybersecurity in the RAILway sector. Retrieved from http: / / shift2rail. org/ projects/ cyrail/  [6] Shift2Rail. (2016). Smart automation of rail transport. Retrieved from http: / / shift2rail. org/ projects/ smart/  [7] Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Boston, MA: Pearson.  [8] Tzafestas, S. G. (1999). Advances in intelligent systems: Concepts, tools, and applications. Dordrecht, The Netherlands: Kluwer Academic.  [9] Boulding, K. E. (1956). General systems theory: The skeleton of science. Management Science, 2(3), 197-208. Reprinted and appendixed: http: / / www.panarchy.org/ boulding/ systems.1956.html [10] Tokody, D. (2016). Okos Mobilitás [Smart Mobility]. Műszaki tudományos közlemények, 5(1), 401-404. [11] Édelkraut, R., et al. (2005). Mesterséges Intelligencia Almanach [Artificial intelligence almanac]. Retrieved from http: / / mialmanach.mit.bme.hu/ aima/ ch01 [12] Arter, M. (2015). It’s looking good: the emerging case for Digital Railway [PowerPoint slides]. Retrieved from http: / / digitalrailway.co.uk/ wp-content/ uploads/ 2016/ 05/ Martin- Arter-Presentation-SupplierConference-20-Nov-15.pptx. [13] International Union of Railways. (2015). A global vision for railway development. Paris, France: International Union of Railways. [14] The Thales Group. (2016). Digitalisation of German railways: Interview with Dr. Ben Möbius [Video file]. Retrieved from https: / / www.youtube.com/ watch? v=ThIViPEmckA [15] European Union Agency for Network and Information Security (ENISA). (2016). IoT and smart infrastructures. Retrieved from https: / / www.enisa.europa.eu/ topics/ iot-andsmart-infrastructures [16] European Commission, Innovation and Networks Executive Agency of the (INEA). (2014). Mission & objectives. Retrieved from https: / / ec.europa.eu/ inea/ en/ mission-objectives Daniel Tokody, Dipl.-Ing. Young Researcher, Investment Project Coordinator, Óbuda University, Doctoral School on Safety and Security Sciences; Hungarian State Railways; Gödöllő (HU) tokody.daniel@dosz.hu Francesco Flammini, Dr. Adjunct Assistant Professor, University of Maryland University College (UMUC) Europe, Rome (IT) francesco.flammini@faculty.umuc.edu