Denna studie handlar om den fartförlust och därmed den ökade energiförbrukningen som drabbar fartyg på grunt vatten. Syftet var att ta reda på hur mycket kortare en grund passage behöver vara för att den ska vara ett bättre alternativ än en lång och djup rutt med hänsyn till bränsleförbrukning och tidsåtgång. Resultatet av detta blev att det inte går att dra några generella slutsatser som gäller för alla fartygstyper men att det går att se tydliga tendenser. Studien hade även som målsättning att skapa ett underlag som skulle kunna användas av nautiker vid planering av resor, detta presenterades i form av en sammanställning av de resultat som erhållits vid beräkning av fartförlust i öppet vatten. Någon sammanställning gjordes inte för begränsat vatten eftersom exempelfartygen där fick likadana resultat vilket skulle ha gjort en sådan överflödig. Syftet uppnåddes genom användande av kvantitativa studier i form av matematiska beräkningsmetoder för att beräkna fartförlust, bränsleförbrukning och tidsåtgång för ett antal exempelfartyg. / This study concerns the speed loss and thereby the increased energy consumption which affects ships in shallow water. The aim of the study was to gain knowledge of how much shorter a shallow passage is required to be in order to be the better alternative compared to a long and deep route with regard to fuel and time consumption. The result was that it is not possible to draw any definitive conclusions which are applicable to all ship types, however, there are clear patterns. Moreover, the goal of the study was to aid mariners facing a choice between a long and deep route and a short and shallow route, this was done by creating a compilation of the results for speed loss in open water. Due to the results for confined waters being the same for all the ships in the study, no compilation was done for confined waters as it was deemed excessive. The aim of the study was achieved by quantitative research in the form of mathematical models to calculate speed loss, fuel consumption and time consumption for a number of fictitious ships.

This article describes the Dana intelligent Twin Steering System designed for mobile vehicles with two steering axles (i.e. with four steering wheels). Current vehicles with four-wheel steering function are typically equipped with a hydraulic configuration where the two steering cylinders are connected in series. This type of connection highlights some limitations on available power, steering comfort and enabling advanced working functions. Dana evolved this type of hydraulic configuration introducing the possibility to disconnect the rear axle from the front one. In this way the rear axle, through the electronic control of its valve block, allows to improve the steering system performance and introduces advanced steering functions compared to the conventional steering systems.

The main content of this thesis is a suggestion of computing system for efficient energy manufacture. The introduction devotes to description of up-to-date waste-to-energy units (EVO), it concentrates on Incinerator of municipal wastes of TERMIZO a.s., specifically. In the main body of this work is the data analysis of factory journal that has been implemented, results have been used as mathematical model output value. These activities are necessary for computing system suggestion. Resulting optimization of batch wasting plan with maximum economic effect for entrepreneur is the main output of this work. Conclusion consists of environmental and economic evaluation of operation of up-to-date waste-to-energy units and offers another optimization posibility.

This study explores the application of multi-agent reinforcement learning (MARL) to enhance the decision-making, safety, and passenger comfort of Autonomous Vehicles (AVs)at uncontrolled intersections. The research aims to assess the potential of MARL in modeling multiple agents interacting within a shared environment, reflecting real-world situations where AVs interact with multiple actors. The findings suggest that AVs trained using aMARL approach with global experiences can better navigate intersection scenarios than AVs trained on local (individual) experiences. This capability is a critical precursor to achieving Level 5 autonomy, where vehicles are expected to manage all aspects of the driving task under all conditions. The research contributes to the ongoing discourse on enhancing autonomous vehicle technology through multi-agent reinforcement learning and informs the development of sophisticated training methodologies for autonomous driving.