https://rep.bntu.by/handle/data/49659 2026-04-09T21:27:04Z https://rep.bntu.by/handle/data/61642 Validation of an Assistance System for Merging Maneuvers in Highways in Real Driving Conditions Sanchez-Mateo, S.; Perez-Moreno, E.; Jimenez, F.; Serradilla, F.; Cruz Ruiz, A.; de la Fuente Tamayo, S. In the latest study conducted by the National Highway Traffic Safety Administration in 2018, it was published that human error is still considered the major factor in traffic accidents, 94 %, compared with other causes such as vehicles, environment and unknown critical reasons. Some driving scenarios are especially complex, such as highways merging lanes, where the driver obtains information from the environment while making decisions on how to proceed to perform the maneuver smoothly and safely. Ignorance of the intentions of the drivers around him leads to risky situations between them caused by misunderstandings or erroneous assumptions or perceptions. For this reason, Advanced Driver Assistance Systems could provide information to obtain safer maneuvers in these critical environments. In previous works, the behavior of the driver by means of a visual tracking system while merging in a highway was studied, observing a cognitive load in those instants due to the high attentional load that the maneuver requires. For this reason, a driver assistance system for merging situations is proposed. This system uses V2V communications technology and suggests to the driver how to modify his speed in order to perform the merging manoeuver in a safe way considering the available gap and the relative speeds between vehicles. The paper presents the results of the validation of this system for assisting in the merging maneuver. For this purpose, the interface previously designed and validated in terms of usability, has been integrated into an application for a mobile device, located inside the vehicle and tests has been carried out in real driving conditions. 2019-01-01T00:00:00Z https://rep.bntu.by/handle/data/61640 Signal Pre-Selection for Monitoring and Prediction of Vehicle Powertrain Component Aging Udo Sass, A.; Esatbeyoglu, E.; Iwwerks, T. Predictive maintenance has become important for avoiding unplanned downtime of modern vehicles. With increasing functionality the exchanged data between Electronic Control Units (ECU) grows simultaneously rapidly. A large number of in-vehicle signals are provided for monitoring an aging process. Various components of a vehicle age due to their usage. This component aging is only visible in a certain number of in-vehicle signals. In this work, we present a signal selection method for in-vehicle signals in order to determine relevant signals to monitor and predict powertrain component aging of vehicles. Our application considers the aging of powertrain components with respect to clogging of structural components. We measure the component aging process in certain time intervals. Owing to this, unevenly spaced time series data is preprocessed to generate comparable in-vehicle data. First, we aggregate the data in certain intervals. Thus, the dynamic in-vehicle database is reduced which enables us to analyze the signals more efficiently. Secondly, we implement machine learning algorithms to generate a digital model of the measured aging process. With the help of Local Interpretable Model-Agnostic Explanations (LIME) the model gets interpretable. This allows us to extract the most relevant signals and to reduce the amount of processed data. Our results show that a certain number of in-vehicle signals are sufficient for predicting the aging process of the considered structural component. Consequently, our approach allows to reduce data transmission of in-vehicle signals with the goal of predictive maintenance. 2019-01-01T00:00:00Z https://rep.bntu.by/handle/data/61639 Increasing the Quality of Transient Processes in the Vehicle Transmission Taratorkin, A.; Derzhanskii, V.; Taratorkin, I. The paper shows results of an experimental and theoretical study of dynamic processes in the vehicle transmission after kinematic alignment of elements during gearshifts. The purpose of the research is increasing the quality of transient processes in the vehicle transmission. Applying an analysis of experimental results obtained through looking into dynamics of a 3-ton vehicle transmission and studying literature sources it was established that dynamic loading of the transmission after the kinematic stage of shifting (i. e. synchronizing speeds of driving and driven elements in the gearbox) is influenced by oscillations which are in the single-node mode. Solving the task of increasing transient processes is achieved by applying a method of control power redistribution. By employing simulation models a number of methods were used to regulate power redistribution. Results of computations made it possible to determine that the efficiency of power redistribution are closely related to initial conditions of the process under the study. In the progress of the research a method for identifying the initial conditions was developed. This method is based determining signatures of the torque and its derivatives. In accordance with the research results it turned out that it is appropriate to apply the ZVD (zero vibration derivation) algorithm of power redistribution for low gears (below 4th) from point of view achieving better overshoot and robustness characteristics and a satisfactory response rate level. For higher gears it is recommended that the Ramp algorithm (linear increase in the control input) be used for the cases when the response rate is not longer than period of the single-node mode of oscillations occurring in the dynamic system during a gear shift. Application of the proposed algorithms allows to bring down dynamic loading of the transmission and also to improve the comfort in vehicles. 2019-01-01T00:00:00Z https://rep.bntu.by/handle/data/61638 The Analysis of Available Data on Energy Efficiency of Electric Vehicles to be Used for Eco-Driving Project Development Maljkovic, M.; Stamenkovic, D.; Blagojevic, I.; Popovic, V. The goal of this paper is to analyse the collected data on energy efficiency of electric vehicles from researches done by other authors and also to summarise all the factors affecting it. The majority of data available are obtained through simulations – therefore the emphasis in this paper will be placed on experimentally acquired data. The results of the analysis will be used for the planned e-bus eco-driving project for the purpose of Belgrade’s public transportation system. Currently there are only 5 (ultracapacitor type) e-buses operating in Belgrade city public transport, which makes only 0.2 % of all vehicles in rolling stock (making 16 % together with other electric-powered vehicles – trams and trolleybuses), but there are plans to acquire new 80 electric buses. With the rise of the number of electric vehicles, appropriate training of drivers is gaining more and more importance, and the results of the presented analysis make the basis for such training. This will hopefully increase the range of the buses used and help save the energy spent by public transportation, thus giving a little contribution to global fight for cleaner planet. 2019-01-01T00:00:00Z