Removing the human factor from transport (in the direct sense) is still a plan, reaching into the future. However, this plan does not require so much imagination - autonomous vehicles can already be found on the roads. Currently, they are not only autonomous but also independent, i.e. decisions about traffic parameters are made in the vehicle. In the future, with more autonomous vehicles, there will be a need to connect them with a communication network, which will eliminate a number of telematic problems. It remains an open question how to make this network? Is it based on the modern Internet network? What and which data will be necessary to achieve the “right relations” between autonomous vehicles (hosts of network)? The article presents one aspect of the mentioned problem; the amount of data generated by an autonomous vehicle is presented in light of the processing capabilities of modern ICT systems.
Implementation of hybrid drives in rail vehicles is a solution aimed at limiting the negative environmental impact of transport. The use of fuel cell systems is a contemporary trend in the development of locomotives. The paper presents an energy flow analysis in a hybrid locomotive powered using fuel cells. The parallel hybrid drive system consisted of fuel cells, batteries and an electric motor. The simulations and analyzes were performed with the use of AVL Cruise M software. A simulated route, with a length of approximately 300 km, was used as basis for the analysis, taking into account a typical speed profile of a locomotive in passenger traffic. The energy flow and consumption values were estimated, and mean hydrogen consumption values were determined.
The article presents analysis of road crash accidents. It presents the evolution of safety systems, starting from a description of the currently used vehicle-based systems, with particular emphasis on the prediction of the driver falling asleep. The article also proposes a proprietary system of sleep prediction based on the face detection of drivers. The detection of facial landmarks is presented as a two-step process: an algorithm finds faces in general, and then needs to localize key facial structures within the face region of interest.
The potential for energy production from effluents and husks generated in grain processing in the rice parboiling industries in Brazil is capable of promoting energy self-sufficiency in the sector, through the production and use of syngas and biogas. However, the production of methane from residues of the rice parboiling industries is still little explored by academic studies, in general studies on the potential of methane production by this same type of effluent are found in the south of the country, however, the same is not true for the production of biodiesel from rice bran oil. The objective of this study was to determine the production potential of biodiesel, methane and electric energy of the largest parboiled rice industry in Rio Grande do Sul, located in the southern region of the country. According to this study, the rice parboiling industry located in Rio Grande do Sul, Brazil, has a production potential of 1.2-10² m³ /day of biodiesel, 2.93-10 Nm³ /day of methane and 1.89-10⁴ kWh/day of electricity. Despite being a significant and high potential, which may reduce the financial expenses of the industry regarding the purchase of energy from concessionaires, it is not able to promote its energy self-sufficiency. At the same time, it would be necessary to add the energy production potential of the rice husk gasification syngas highlighted in other studiem.
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