Effective fleet management is related to the care for their rational use and proper diagnostics. Early detection of potential irregularities enables to prevent failures and carry out transport processes in an undisturbed way. One of the most important components, from the safety point of view, is the braking system. Laboratory tests can be used to determine the durability characteristics of individual components. Individual indications referring to operating conditions would be most desirable. The article, based on a two-year period of testing of a group of Renault vehicles fitted with disc brakes, presents measurement of wearing and tearing the system components (brake discs and brake friction insert) in a function of selected factors, depending on the time and environment in which the transport was carried out. Nonparametric statistical tests were used to analyze the results. Mann-Whitney and Kruskal-Wallis tests were used to verify the hypothesis on the insignificance of differences. Their results were compared with the results of ANOVA variance analysis. The significance of factors influencing the degree of brakes wear was checked. Possible directions of using the results of brake wear measurement for rationalization of transport processes were also indicated. Presented method may also be applied to the evaluation of other components (assemblies, subassemblies, systems) of motor vehicles.

Transport companies can be regarded as a technical, organizational, economic and legal transport system. Maintaining the quality and continuity of the implementation of transport requisitions requires a high level of readiness of vehicles and staff (especially drivers). Managing and controlling the tasks being implemented is supported by mathematical models enabling to assess and determine the strategy regarding the actions undertaken. The support for managing processes relies mainly on the analysis of sequences of the subsequent activities (states). In many cases, this sequence of activities is modelled using stochastic processes that satisfy Markov property. Their classic application is only possible if the conditional probability distributions of future states are determined solely by the current operational state. The identification of such a stochastic process relies mainly on determining the probability matrix of interstate transitions. Unfortunately, in many cases the analyzed series of activities do not satisfy Markov property. In addition, the occurrence of the next state is affected by the length of time the system remains in the specified operating state. The article presents the method of constructing the matrix of probabilities of transitions between operational states. The values of this matrix depend on the time the object remains in the given state. The aim of the article was to present an alternative method of estimating the parameters of this matrix in a situation where the studied series does not satisfy Markov property. The logistic regression was used for this purpose.

This article uses Markov and semi-Markov models as some of the most popular tools to estimate readiness and reliability. They allow to evaluate of both individual elements as well as entire systems—including production systems—as multi-state structures. To be able to distinguish states with varying degrees of technical readiness in complicated and complex objects (systems) allows to determine their individual impact on the tasks performed, as well as on the total reliability. The application of the Markov process requires, for the process dwell times in the individual states, to be random variables of exponential distribution and the fulfilling Markov’s property of the independence of these states. Omitting these assumptions may lead to erroneous results, which was the authors’ intention to show. The article presents a comparison of the results of the examination of the process of non-parametric distribution with an analysis in which its exponential form was (groundlessly) assumed. Significantly different results were obtained. The aim was to draw attention to the inconsistencies obtained and to the importance of a preliminary assessment of the data collected for examination. The diagnostics of the machine readiness operating in the studied production company was additionally performed. This allowed to evaluate its operational potential, especially in the context of solving process optimization problems.

A special element of road safety research is accidents at the interface of the road and rail system. Due to their low share in the total number of incidents, they are not a popular subject of analyses but rather an element of collective studies, whereas the specificity of the road–rail accidents requires a separate characteristic, allowing, on the one hand, to categorize these types of incidents, and on the other, to specify the factors that affect them, along with an assessment of the strength of this impact. It is important to include in such analyses all potential predictors, both qualitative and quantitative. Moreover, the literature considers most often a number of accidents while, according to the authors, it does not fully reflect the scale of the danger. A better evaluation would be the victim’s degree of injury. Therefore, the purpose of this article is to assess the likelihood of occurrence of various effects of road–rail accidents in the aspect of selected factors. Due to the ordinal form of the dependent variable, the classification trees method was used. The results obtained not only allow the characterization and assessment of the danger but also constitute guidelines for taking preventive actions.

In the paper authors presented concept of evaluation of complex systems such as logistic companies which operate in competitive environment. Authors also highlighted the importance of the evaluation problem in operational activity, particularly in the properly prepared procedures to be followed, consisted of several stages adapted to currently conducted research. Properly executed evaluation of companies enables customers to take right decisions on contracting services and stimulate the development of those companies. It should be noted that the proposed algorithmic model of assessment may be particularly useful for assessment of complex logistics systems. Characteristics of the respective phases developed procedure allowed to indicate that it is important to select of appropriate criteria and evaluation methods. It was pointed out that particularly useful for assessing of logistics companies are multi-criteria analysis methods, because they allow to examine objects in a holistic manner, taking into consideration various aspects of activities such organizations. For the practical realization of assessment of logistics companies there was proposed Bellinger method, which contains quite transparent procedures. The results obtained from that method are consistent with those carried out by means of other, more complex multi-criteria methods. Also there was presented the problem of selection of weighted factors for the criteria in the context of their impact on the end result of evaluation. It was pointed out that the choice of an appropriate procedure for determining weights depends on the nature of the evaluated problem and form of criteria.

Assessing vehicle emissions is crucial for understanding their environmental impact and developing effective emission reduction strategies. This article discusses modern research tools that combine traditional laboratory measurements on chassis dynamometers with advanced theoretical models. Probabilistic methods, including stochastic processes based on Markov and semi-Markov chains, are important tools for modelling driving cycles, considering the variability of road conditions and driver behaviour. The article also presents mathematical approaches to emission data analysis, considering both the states of the technical system and the transitions between them, which allows for precise modelling of real vehicle operating conditions. Ultimately, the synergy of experimental measurements with computational modelling offers a more complete and accurate tool for assessing pollutant emissions, which is crucial in global efforts to improve air quality.