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.

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Abstract. Vehicle gearbox dynamics is characterized by time varying mesh stiffness. The paper presents a survey of methods used for determining mesh stiffness and the analysis of the centre distance influence on it. The refined mathematical transmission model presenting the centre distance as a variable is presented. The centre distance error as well as backlash and bearing flexibility is defined and the influence of these factors on mesh stiffness and spur gear dynamics is investigated. The results obtained from this paper may be used in gear-box diagnostics.

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The article examines a mathematical model for the system 'Railway Vehicle Wheel-Track' that allows examining the interaction between a wheel flat and a rail in the vertical plane. The dynamics of the railway track is described using the finite element method while that of the soil and vehicle is expressed applying discrete elements. The model is used for assessing physical and mechanical properties, the roughness of the wheel, rail surface and their geometry. The analysis of the dynamic system 'Railway Vehicle Wheel-Track' has been conducted. In accordance with the revised method, forces arising from contact between the wheel flat and the rail are possible to be determined in a more precise way. The article presents and analyses the results of a mathematical experiment on this system.

Railway infrastructure must meet safety requirements concerning its construction and operation. Track geometry monitoring is one of the most important activities in maintaining the steady technical conditions of rail infrastructure. Commonly, it is performed using complex measurement equipment installed on track-recording coaches. Existing low-cost inertial sensor-based measurement systems provide reliable measurements of track geometry in vertical directions. However, solutions are needed for track geometry parameter measurement in the lateral direction. In this research, the authors developed a visual measurement system for track gauge evaluation. It involves the detection of measurement points and the visual measurement of the distance between them. The accuracy of the visual measurement system was evaluated in the laboratory and showed promising results. The initial field test was performed in the Vilnius railway station yard, driving at low velocity on the straight track section. The results show that the image point selection method developed for selecting the wheel and rail points to measure distance is stable enough for TG measurement. Recommendations for the further improvement of the developed system are presented.

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Selection of a terrain vehicle for performing different tasks is an important factor, which influences the mobility of a user through the quality of conducting transport activities. This paper is dealing with the problem of the terrain vehicle selection for the equipping of military units which, are to be engaged in multinational operations, using the Analytical Hierarchy Process (AHP) method and Data Envelopment Analysis (DEA). Determination of the relative importance of criteria, which are used for evaluation of potential alternatives is conducted through AHP method. The results proposed by the AHP method are used as multiple outputs of the defined DEA model for the selection of the terrain vehicle. Based on the DEA model the efficiencies of alternatives are defined and also the final ranking of alternatives is determined. Besides the hybrid model AHP-DEA, which is the integral part of a basic multicriteria model in this paper the possible applications of Best Worst Method (BWM) and FUll COnsistency Model (FUCOM) are presented through validation of models. The validation is conducted through statistical data obtained by application of different multicriteria techniques, using Spearman’s Correlation Coefficient (SCC).