International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

This paper examines an innovative approach for modeling the influence of climate parameters on transport infrastructure using artificial neural networks. Through them, detailed climatic data are generated by geographical positions and monthly and annual maps are created for Bulgaria’s territory using the following parameters: surface temperature, diffuse fraction, horizontal solar irradiation, and average albedo of the terrain. Average ground temperature and monthly solar irradiation are essential for maintenance planning and developing strategies to adapt to extreme weather conditions, such as heat waves or frost, which can affect the condition and performance of the road surface. Average monthly temperatures can be used to design effective systems to prevent icing of road surfaces and improve drainage systems. By demonstrating the capabilities of accurate modeling and analysis, this paper highlights the importance of applying artificial neural networks in planning and improving the resilience of transport infrastructure against climate change.

This paper examines an approach using artificial neural networks for innovative modeling of solar data that is needed to realize solar applications for transport infrastructure purposes. Through this modeling, detailed solar data are generated by geographical positions, and monthly and annual maps are created for the territory of Bulgaria for horizontal solar irradiation with its diffuse and direct components and for inclined and reflected solar irradiation, according to Norio Igawa’s model. Diffuse fraction and horizontal and inclined solar irradiation can be helpful in designing solar applications in road infrastructure, such as power signaling systems and street lighting. By demonstrating the capabilities of accurate modeling and analysis of solar data, this paper highlights the importance of applying artificial neural networks in planning and improving the resilience of transport infrastructure against climate change. Using solar energy in transport infrastructure reduces carbon emissions and strengthens environmental sustainability.

The article focuses on issues related to the assessment and interpretation of existing data on crisis events in the context of transport infrastructure. In the face of global climate change, analyzing these data becomes increasingly complex and requires in-depth consideration. The main challenges the paper addresses include the lack of comprehensive and up-to-date data, limited opportunities to analyze causal relationships between climate events and their impact on transport infrastructure, and shortcomings in existing analysis methodologies. The authors call for the development of new, more efficient methods of data collection and analysis that can serve as a basis for future strategic decisions.

This paper focuses on actual knowledge of the effects of changes in infrastructure on modal split of different transport modes, as well as on knowledge of long-term evolution of modal split in areas with dynamic development of transport systems. Further it focuses on studies on relations between modal split and greenhouse emissions and on studies on social factors influencing travel behaviour. Important part of this article are summarisations of articles about changes of travel behaviour of inhabitants of locations, where was opened new transport infrastructure, with focus on new infrastructure intended for public transport.

Transport infrastructure brings together conventional groundwork and innovative technologies in order to improve various aspects of transport system management and control. It enables anticipatory maintenance, planning and scheduling, resource management and aims to improve reliability and safety, increased capacity and asset utilization, better energy efficiency and lower emissions, higher customer service levels and increased economic feasibility. Transport infrastructures have long service life and great costs of building, manning, operating and maintaining throughout their life. Innovation and technology shifts proved to be important factors determining great changes in infrastructure potential and even determine its obsolescence. It is regarded as a concern throughout infrastructure’s entire life cycle and reflects changes in expectation regarding performances in functioning, safety and environmental effects.
Performance and failure are illustrated conceptually and represented in a simplified form considering the evolution of technology, the influence of innovation breeding new generation rail infrastructure, all the way through infrastructure’s service life.
According to the identified particularities, recommendations are to be made in order to insure a best practice in lifecycle management and transport infrastructure renewal in the context of improved reliability, safety and efficiency.

Until Currently in the countries of Europe there is an intensification of the introduction of modern microprocessor systems of railway automation and the increase of their functional capabilities. The introduction of additional functions of control and monitoring systems, tightening of the requirements for the safety of their operation, mutual integration and unification of systems for various purposes, the complication of the implementation of processing of logical dependencies require fundamentally new approaches to the development of software and hardware of a new generation. In this regard, scientific and applied research aimed at the development of appropriate technologies is being conducted, based on the common methods and tools used in the formation of control and monitoring systems for various objects of the railway transport infrastructure. The proposed material contains the main results of such studies conducted over the past five years, as well as the main directions for further improving the development of microprocessor-based rail automation systems.