The rationalization of logistics activities and processes is very important in the business and efficiency of every company. In this respect, transportation as a subsystem of logistics, whether internal or external, is potentially a huge area for achieving significant savings. In this paper, the emphasis is placed upon the internal transport logistics of a paper manufacturing company. It is necessary to rationalize the movement of vehicles in the company's internal transport, that is, for the majority of the transport to be transferred to rail transport, because the company already has an industrial track installed in its premises. To do this, it is necessary to purchase at least two used wagons. The problem is formulated as a multi-criteria decision model with eight criteria and eight alternatives. The paper presents a new approach based on a combination of the Simple Additive Weighting (SAW) method and rough numbers, which is used for ranking the potential solutions and selecting the most suitable one. The rough Best-Worst Method (BWM) was used to determine the weight values of the criteria. The results obtained using a combination of these two methods in their rough form were verified by means of a sensitivity analysis consisting of a change in the weight criteria and comparison with the following methods in their conventional and rough forms: the Analytic Hierarchy Process (AHP), Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS) and MultiAttributive Border Approximation area Comparison (MABAC). The results show very high stability of the model and ranks that are the same or similar in different scenarios.

A decision-making process often requires knowledge of numerous parameters and their interaction in order to make valid decisions that will result in meeting the objectives set. Multi-criteria decision-making is an area that helps in decision-making processes considering a set of criteria and alternatives. A new MCDM approach has been developed in this paper with a view to better managing the uncertainties and the subjectivity of real decision problems. In the last few years, the integration of Rough numbers and multi-criteria decision-making methods has enjoyed a great popularity, so in this paper, the Rough Step-wise Weight Assessment Ratio Analysis (SWARA) approach has been developed. The developed approach has been verified throughout a sensitivity analysis, which involves the comparison of the obtained results with two other methods for determining the weight values, the Rough Best Worst method (BWM) and Rough Analytic Hierarchy Process (AHP). The correlation of obtained ranks using the Rough SWARA approach with the ranks of Rough BWM and Rough AHP is complete, i.e. the ranks are identical, which confirms the stability and credibility of the developed approach.

Nowadays, vehicles have advanced driver-assistance systems which help to improve vehicle safety and save the lives of drivers, passengers and pedestrians. Identification of the road-surface type and condition in real time using a video image sensor, can increase the effectiveness of such systems significantly, especially when adapting it for braking and stability-related solutions. This paper contributes to the development of the new efficient engineering solution aimed at improving vehicle dynamics control via the anti-lock braking system (ABS) by estimating friction coefficient using video data. The experimental research on three different road surface types in dry and wet conditions has been carried out and braking performance was established with a car mathematical model (MM). Testing of a deep neural networks (DNN)-based road-surface and conditions classification algorithm revealed that this is the most promising approach for this task. The research has shown that the proposed solution increases the performance of ABS with a rule-based control strategy.

The daily requirements and needs imposed on the executors of logistics services imply the need for a higher level of quality. In this, the proper execution of all sustainability processes and activities plays an important role. In this paper, a new methodology for improving the measurement of the quality of the service consisting of three phases has been developed. The first phase is the application of the Delphi method to determine the quality dimension ranking. After that, in the second phase, using the FUCOM (full consistency method), we determined the weight coefficients of the quality dimensions. The third phase represents determining the level of quality using the SERVQUAL (service quality) model, or the difference between the established gaps. The new methodology considers the assessment of the quality dimensions of a large number of participants (customers), on the one hand, and experts’ assessments on the other hand. The methodology was verified through the research carried out in an express post company. After processing and analyzing the collected data, the Cronbach alpha coefficient for each dimension of the SERVQUAL model for determining the reliability of the response was calculated. To determine the validity of the results and the developed methodology, an extensive statistical analysis (ANOVA, Duncan, Signum, and chi square tests) was carried out. The integration of certain methods and models into the new methodology has demonstrated greater objectivity and more precise results in determining the level of quality of sustainability processes and activities.

Traffic safety may be ensured by normal operation of all elements of the system, including the driver, a motor vehicle and transportation medium. Insufficient safety of some particular elements of this system (the lack of discipline of the participants of traffic, poor technical state of a motor vehicle or road, etc.) are the main causes of traffic accidents. Statistical data on traffic accidents in 2000–2009 in Lithuania is presented. Collisions of motor vehicles in 2009 make one of the largest proportion of all traffic accidents ‐ 33.4%. In 2009 drivers, were the main traffic accident perpetrators ‐ 73.6%. The paper considers some major aspects of motor vehicle collision simulation based on the application of PC‐CRASH software, allowing researchers to analyze the changes in the direction of motor vehicle motion in the case of a collision and the influencing factors. This type of traffic accident simulation consists in studying the circumstances of collision, reconstructing the processes, calculating the pre‐impact speed of motor vehicles and deter‐ mining various parameters of motor vehicles’ movement at different stages of traffic accident development.