David Jozsa

56941878000

Publications - 7

Development of a Diagnostic Procedure for Vehicle’s Built-in Electric Motors †

David Jozsa Marton Jagicza Gabor Laszlo Toth Balázs Baráth

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Electric and hybrid vehicles, similarly to combustion engine ones, can experience malfunctions, yet preventive diagnostics for their electric motors are underdeveloped. While many methods exist for testing electric motors in heavy industry, they are not commonly applied in the vehicle industry. Our study aims to develop a real-time, non-invasive fault detection procedure for electric motors in these vehicles. Previous research has focused on simulations, but our work involves real measurements conducted in a controlled laboratory using a two-axle chassis dyno. We present the hybrid vehicle’s drivetrain, our equipment, and the feasibility of simulated methods, and we also detail the evaluation method used.

Open Access: Yes

DOI: 10.3390/engproc2024079004

Vehicle in the Loop Testing of Traffic Sign Recognition Systems †

David Jozsa Marton Jagicza Richárd Peszleg

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Modern passenger vehicles can indicate the speed limit for a given road section using GPS, cameras, or both. Sign recognition systems must comply with specified testing procedures before operation. Our goal is to create a cost-effective lab environment for vehicle-level tests of these systems. Image recognition can be tested with various traffic signs in a simulation video placed in front of the vehicle’s camera while it runs on a chassis dyno. We tested this environment with factory-built systems, displaying recognized signs on the dashboard. The simulation software allows unlimited signs, eliminating the need for long-distance driving or extensive test track setups. While the lab environment does not replace final public road testing, it is a cost-effective solution for the development and testing of traffic sign recognition systems.

Open Access: Yes

DOI: 10.3390/engproc2024079074

Measurement of Pedestrian Targets in Terms of Radar Cross Section

David Jozsa Leticia Pekk Marton Jagicza Gabor Laszlo Toth Denes Fodor

Publication Name: Saci 2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 363-368

Description:

In terms of vehicle radars, the most important properties of targets are speed, distance, and radar cross section. Based on the Radar Cross Section (RCS), the type of the object can be identified with a good approximation: pedestrian, bicycle, car, truck even in extreme weather conditions. A radar cross section measures the reflectivity of an object and its numerical value is equal to the area of the cross section of a conducting sphere with the same reflectivity. Its value depends on the material and shape of the object, the angle of illumination, and the ratio between the wavelength and the size of the object. The article presents a measurement system for radar targets, the main component of which is an automotive radar. In addition, the evaluation software for the measurement system, which was created in the MATLAB / SIMULINK environment, will be presented. The measurement system was used to perform various measurements on the ZalaZONE Automotive Proving Ground (Zalaegerszeg, HUNGARY), the evaluation of which will be presented. The purpose of the measurements is to collect information about the radar cross-section values of pedestrians at different distances from the vehicle and dummies simulating them. A comparison of different pedestrians is presented. After that, we will show how even if a puppet is formally similar to a pedestrian, the RCS can show a different value.

Open Access: Yes

DOI: 10.1109/SACI58269.2023.10158601

Spectral Analysis of the Lateral Dynamics of Road Vehicles †

David Jozsa Dániel Pup György Istenes Gergo Igneczi József Bokor

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

In this paper, a time domain and a spectral analysis of the lateral dynamics of a Lexus passenger car are presented. Measurements were made of the vehicle’s lateral acceleration and steering angle. The aim of the measurements is to understand the vehicle’s lateral dynamics during different cornering maneuvers. For this purpose, part of the measurements is performed with a driver and the other part with autonomous control. The data processed and analyzed in this research can be used to determine the nature of the lateral dynamics, which is essential to establishing a mathematical relationship between the measured signals. This will allow the identification and modeling of vehicle dynamics, which is key to the development and optimization of autonomous vehicle control systems.

Open Access: Yes

DOI: 10.3390/engproc2025113063

Lightweight Solution to Generate Accurate Lanelet Maps †

David Jozsa Gergo Igneczi Matyas Mesics

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

As automated driving technologies become more mature, there is an increasing reliance on digital maps to support safe and efficient driving. Sensors like cameras and radars can be limited by occlusions, lighting conditions, or weather, and often fall short. High-definition (HD) maps offer excellent accuracy, but they are expensive to produce. These limitations make these techniques impractical for large-scale deployment. What makes our approach particularly attractive is its hardware simplicity: the entire process requires only a precise GNSS receiver and a commonly available lane detection camera, eliminating the need for expensive sensors like LiDAR or complex multi-vehicle fleets. We rigorously evaluated our method in a highway environment, where a vehicle equipped with our generated maps successfully executed autonomous lane following and adapted its speed based on detected speed limit signs. The positional deviation of the resulting maps was consistently under 5 cm.

Open Access: Yes

DOI: 10.3390/engproc2025113068

Analysis of Following Distance Measurement and Compliance in Road Traffic

David Jozsa Richárd Peszleg Tibor Cseke Máté Ihász

Publication Name: Engineering Perspective

Publication Date: 2025-12-28

Volume: 5

Issue: Special Issue

Page Range: 14-17

Description:

The study examines the observance of safe following distances under real traffic conditions. Maintaining an appropriate following distance plays a key role in accident prevention, as it gives drivers sufficient time to perceive hazards and react appropriately. To record empirical data, a rear radar sensor was installed on the test vehicle, which continuously measured the distance and speed of the vehicle behind. This method allowed for a detailed analysis of how the following distance changes as a function of speed. The collected data was compared with the minimum safety requirements based on reaction time and braking performance described in the literature. The comparison shows the extent to which actual driver behavior deviates from the recommended safety standards. Although modern vehicles are increasingly equipped with driver assistance systems, such as automatic emergency braking, the vast majority of vehicles in Hungary are not yet equipped with such systems. As a result, road safety depends largely on individual driver decisions and compliance with the rules. The results highlight the potential accident risks arising from inadequate following distances, especially in everyday traffic situations where drivers often underestimate the distance required for a safe stop. The measurement result show that most drivers following distance is shorter than the average stopping distance. The research contributes to a deeper understanding of domestic driving habits and provides a basis for the development of road safety campaigns, driver training programs, and possible regulatory measures. Overall, the results emphasize the importance of maintaining a safe following distance as a simple, cost-effective, and efficient means of improving road safety.

Open Access: Yes

DOI: 10.64808/engineeringperspective.1791630

Determination of the Centre of Gravity of Electric Vehicles Using a Static Axle-Load Method

David Jozsa Balázs Baráth

Publication Name: Future Transportation

Publication Date: 2026-02-01

Volume: 6

Issue: 1

Page Range: Unknown

Description:

Accurate determination of a vehicle’s centre of gravity (CoG) is fundamental to driving dynamics, safety, and engineering design. However, existing static CoG estimation methods often neglect tyre deflection and detailed wheel geometry, which can introduce significant errors, particularly in electric vehicles, where the low and concentrated mass of the battery pack increases the sensitivity of vertical CoG calculations. This study presents a refined static axle-load-based method for electric vehicles, in which the influence of tyre deformation and lifting height on the accuracy of the vertical centre of gravity coordinate is explicitly considered and quantitatively justified. To minimise human error and accelerate the evaluation process, a custom-developed Python (Python 3.13.2.) software tool automates all calculations, provides an intuitive graphical interface, and generates visual representations of the resulting CoG position. The methodology was validated on a Volkswagen e-Golf, demonstrating that the proposed approach provides reliable and repeatable results. Due to its accuracy, reduced measurement complexity, and minimal equipment requirements, the method is suitable for design, educational, and diagnostic applications. Moreover, it enables faster and more precise preparation of vehicle dynamics tests, such as rollover assessments, by ensuring that sensor placement does not interfere with vehicle behaviour.

Open Access: Yes

DOI: 10.3390/futuretransp6010022