New technologies reaching out for meeting the needs of an aging population in developed countries have given rise to the development and gradual implementation of the concept of an autonomous vehicle (AV) and have even made it a necessity and an important business paradigm. However, in parallel, there is a discussion about consumer preferences and the willingness to pay for new car technologies and intelligent vehicle options. The main aim of the study was to analyze the impact of selected factors on the perception of the future of autonomous cars by respondents from the area of Southeastern Poland in terms of a comparison with traditional cars, with particular emphasis on the advantages and disadvantages of this concept. The research presented in this study was conducted in 2019 among a group of 579 respondents. Data analysis made it possible to identify potential advantages and disadvantages of the concept of introducing autonomous cars. A positive result of the survey is that 68% of respondents stated that AV will be gradually introduced to our market, which confirms the high acceptance of this technology by Poles. The obtained research results may be valuable information for governmental and local authorities, but also for car manufacturers and their future users. It is an important issue in the area of shaping the strategy of actions concerning further directions of development on the automotive market.

Taking into consideration the fact that used oils are considered hazardous and extremely toxic, their subsequent use creates a real threat to the environment. The only effective measure for protecting the natural environment from used oil contamination is collection and controlled utilization. Only appropriate used oil management can guarantee minimal environmental contamination and prevent its irreversible degradation. The aim of our study was to determine the content of select heavy metal elements in used engine oils originating from agricultural tractors and agricultural machines of varying mileage. The tests were carried out by using the HD XRF method. The researched samples showed a high content of zinc remaining at 726- 1,389 mg·kg^-1. The contents of molybdenum, iron, and copper also were high, at Mo 360-689 mg·kg^-1, Fe 16.5- 267 mg·kg^-1, and Cu 4.63-76.87 mg·kg^-1. Low nickel, manganese, chromium, and lead contents were found in the ranges: Ni 0.14-0.75 mg·kg^-1, Mn 0.41-4.27 mg·kg^-1, Cr 0.36-10.66 mg·kg^-1, and Pb 0.9-13.71 mg·kg^-1. Mercury and cadmium were not found in the tested oils.

In this paper, we focus on detection of speed changes from audio data, representing recordings of cars passing a microphone placed near the road. The goal of this work is to observe the behavior of drivers near control points, in order to check whether their driving is safe both when approaching the speed camera and after passing it. The audio data were recorded in controlled conditions, and they are publicly available for downloading. They represent one of three classes: car accelerating, decelerating, or maintaining constant speed. We used SVM, random forests, and artificial neural networks as classifiers, as well as the time series based approach. We also tested several approaches to audio data representation, namely: average values of basic audio features within the analyzed time segment, parametric description of the time evolution of these features, and parametric description of curves (lines) in the spectrogram. Additionally, the combinations of these representations were used in classification experiments. As a final step, we constructed an ensemble classifier, consisting of the best models. The proposed solution achieved an accuracy of almost 95%, without mistaking acceleration with deceleration, and very rare mistakes between stable speed and speed changes. The outcomes of this work can become a basis for campaigns aiming at improving traffic safety.

The manuscript describes the results of an experimental study of the level of PM (particulate matter) emissions arising from the combustion of two selected types of biomass (i.e., rapeseed straw pellets and engine biofuel (biodiesel, FAME)), which were derived from rapeseed. The PM emissions from the combustion of biofuels were compared with those obtained from the combustion of their traditional counterparts (i.e., wood pellets and diesel fuel). Both types of pellets were burned in a 10 kW boiler designed to burn these types of fuels. The engine fuels tested were burned in a John Deere 4045TF285JD engine mounted on a dynamometer bench in an engine dyno, under various speed and load conditions. A Testo 380 analyzer was used to measure the PM emission levels in boiler tests, while an MPM4 particle emission meter was used in the engine tests. The combustion (under rated conditions) of rapeseed straw pellets resulted in a significant increase in PM emissions compared to the combustion of wood pellets. The PM emissions during the combustion of wood pellets were 15.45 mg·kg⁻¹, during the combustion of rapeseed straw pellets, they were 336 mg·kg⁻¹, and the calculated emission factors were 44.5 mg·MJ⁻¹ and 1589 mg·MJ⁻¹, respectively. In the engine tests, however, significantly lower particulate emissions were obtained for the evaluated biofuel compared to its conventional counterpart. The combustion of rapeseed oil methyl esters resulted in a 40–60% reduction in PM content in the exhaust gas on average for the realized engine speeds over the full load range compared to the combustion of diesel fuel.