Karol Hrudkay

Accurate traffic prediction is crucial for urban planning, especially in rapidly growing cities. Traditional models often struggle to account for sudden traffic pattern changes, such as those caused by the COVID-19 pandemic. Neural networks offer a powerful solution, capturing complex, non-linear relationships in traffic data for more precise prediction. This study aims to create a neural network model for predicting vehicle numbers at main intersections in the city. The model is created using real data from the sensors placed across the city of Zilina, Slovakia. By integrating pandemic-related variables, the model assesses the COVID-19 impact on traffic flow. The model was developed using neural networks, following the data-mining methodology CRISP-DM. Before the modelling, the data underwent thorough preparation, emphasising correcting sensor errors caused by communication failures. The model demonstrated high prediction accuracy, with correlations between predicted and actual values ranging from 0.70 to 0.95 for individual sensors and vehicle types. The results highlighted a significant pandemic impact on urban mobility. The model’s adaptability allows for easy retraining for different conditions or cities, making it a robust, adaptable tool for future urban planning and traffic management. It offers valuable insights into pandemic-induced traffic changes and can enhance post-pandemic urban mobility analysis.

In a smart city, sensors are essential elements—the source of up-to-date traffic information. This article deals with magnetic sensors connected to wireless sensor networks (WSNs). They have a low investment cost, a long lifetime, and easy installation. However, it is still necessary to disturb the road surface locally during their installation. All road lanes to and from the city center of Žilina have sensors that send data at five-minute intervals. They send up-to-date information about the traffic flow’s intensity, speed, and composition. The LoRa network ensures the data transmission, but in the event of failure, the 4G/LTE modem realizes the backup transmission. The disadvantage of this application of sensors is their accuracy. The research task was to compare the outputs from the WSN with a traffic survey. The appropriate method for the traffic survey on the selected road profile is a video recording and speed measurement using the Sierzega radar. The results show distorted values, mainly for short intervals. The most accurate output from magnetic sensors is the number of vehicles. On the other hand, traffic flow composition and speed measurement are relatively inaccurate because it is not easy to identify vehicles based on dynamic length. Another problem with sensors is frequent communication outages, which cause an accumulation of values after the outage ends. The secondary objective of the paper is to describe the traffic sensor network and its publicly accessible database. In the end, there are several proposals for data usage.

This paper aims to analyze the recent development of taxi services in Slovakia on two levels. The first is the area of technological change, which includes the use of digital platforms for the closing of the contract between the passenger and the taxi operator. The second level of perspective is the legislative change. Commonly used taxi digital platforms (applications) have started to require a taxi concession from self-employed drivers, and many other requirements. We will also analyze the issue of value-added tax. This article processes quantitative data on the number of valid taxi concessions. The data were obtained from the unified information system in road transport and supplemented with other statistical inputs. The article describes the distribution of more than 6819 issued concessions in individual regions and analyzes 12,477 taxi vehicles registered in these licenses for operating a taxi service. This article also includes the numbers of performed technical and emission inspections of taxi vehicles. With these data, it is possible to prove a sharp increase in interest in the concession due to the introduction of digital applications. A significant change in business conditions in this area can lead to an increase in the number of businesses by 70% in larger cities, while the issue of sustainability is questionable. In the last part, the article also deals with the issue of electromobility, and environmental aspects connected with taxi legislation changes.

This paper deals with implementation of artificial neural network in the maximum power point tracking (MPPT) controller algorithm for modern household where electric vehicle (EV) was purchased. The proposed MPPT algorithm was designed to achie...

Tento príspevok je zameraný na výskum vplyvu okolitej teploty na spotrebu elektrickej energie elektrobusov. Východiskovým podkladom výskumu bola detailná databáza prevádzkových údajov a taktiež záznamy o priemernej teplote v mieste prevádzky elektrobusov. V úvode rozoberáme aj postupný nástup technológie elektrobusov v Slovenskej republike a mapujeme zloženie vozidlového parku. V tomto prípade sme analyzovali vozidlá Škoda Perun 26SH01, pričom sme sa zamerali na zimnú a letnú prevádzku. Analyzované mesiace boli výrazne odlišné priemernou dennou teplotou. Tá má zásadný vplyv na celkovú spotrebu elektrobusu, pretože analyzovaný typ má kabínu cestujúcich vykurovanú práve elektrickými ohrievačmi. V článku odpovedáme na niekoľko výskumných otázok súvisiacich so spotrebou elektrobusov v našich podnebných podmienkach.

This paper focuses on the statistical evaluation of various operating characteristics of electric buses. The data obtained for statistical evaluation come from practice. In this paper, we focus on electricity consumption—an important aspect of electric bus operation. The ambient temperature significantly affects electricity consumption. In this paper, we use applied mathematics—correlation analysis, we accurately identify the effect of temperature on the consumption of the electric bus. Our next goal was to define the relationship between the loss of energy from the battery and driving power. We used regression analysis to describe this relation. Our article also includes an example of the practical use of ANOVA analysis in identifying a statistically significant effect of a particular vehicle on average consumption. We also show results from previous research and compare two different types of electric buses in operation.