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The article suggests a system dynamics model for estimating the demand for public transport. Traditional scientific and technical transport modeling approaches involve coherent systems, meticulously considering other impactful variables for transport modeling. The vastness of the variables and their combinations hinder us from grasping all possible system interactions. This research aims at proposing a model that comprises decisive factors in relation to the supply and demand in various modes of transport, designing likely scenarios of the transport system development in a specific transport territory. The model uses system dynamics tools to explore the interaction between individual system elements and transport subsystems. A wise choice of crucial system elements, well-adjusted relationships and behavior settings, as well as system dynamics tools, allow for a considerable simplification of an otherwise complex system. The article works with a principle of stock and flow diagrams for forecasting supply and demand in public transport. We take into consideration the implementation of a 'demand index' in public and car passenger transport with a subsequent comparison. This innovative approach monitors the development of a regional or municipal transport system while assessing its sustainability. Suggested demand indexes may serve as indicators for a sustainable municipal system. The suggested model reflects data from the South Bohemian region in the Czech Republic and may involve other elements and indicators of a sustainable transport system. [ABSTRACT FROM AUTHOR]

This article investigates the utilization of eye-tracking methodology to monitor the driver's activities and attention during the arrival and departure procedures of train operations on Slovak Railway (ŽSR) line no. 120, Bratislava–Žilina. Previous studies conducted in 2020 formed the basis of the current research, which focused on two train stations and two railway stops located on the Žilina–Púchov track section. The results of the experiment allowed for a greater understanding of the driver's cognitive processes, thereby leading to increased safety and sustainability in the railway transport system. It is noteworthy that the employed measurement methodology and technology had no detrimental effect on train operation, or operational and thus passenger safety. Thus, the results of this experiment provide a sound foundation for further exploration into human–machine (driver–train) interaction in actual traffic conditions. [ABSTRACT FROM AUTHOR]