Dániel Pup

57190306847

Publications - 17

Towards Robust LIDAR Lane Clustering for Autonomous Vehicle Perception in ROS 2

R. C. Pozna Ernö Horváth Dániel Pup Miklos Unger

Publication Name: Proceedings 2024 IEEE International Conference on Mobility Operations Services and Technologies Most 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 229-234

Description:

From LIDAR pointclouds traffic lanes, racetracks, parking lanes can be extracted with clustering algorithms. However, standard clustering algorithms like DBSCAN, K-means, and BIRCH may exhibit limited robustness in recognizing these specific geometric patterns. The current paper proposes a modification of the well-known DBSCAN algorithm which is designed for autonomous vehicle lane detection. The main idea of the proposed work is to add extra steps into the classic DBSCAN algorithm, thus regulate the cluster expansion. This modification introduces some challenges too, their subsequent resolution will be addressed in detail. To reproduce our work, both the dataset and the accompanying source code in python is shared publicly.

Open Access: Yes

DOI: 10.1109/MOST60774.2024.00031

Nonlinear Identification of Lateral Dynamics of an Autonomous Car Vehicle †

Dániel Pup György Istenes Ferenc Szauter J. Bokor

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this paper, the nonlinear identification of the lateral dynamics of a road vehicle and the velocity dependence of the dynamics are presented. One of the most useful methods to define the mathematical model is system identification based on measured data. A test vehicle for autonomous driving was constrained to move in a straight line while the vehicle’s steering servo was artificially excited. The input of the system is therefore the sum of the artificial excitation and the control signal of the autonomous function, and the output is the lateral acceleration of the vehicle. The measurements are used to identify Wiener and Hammerstein models of the lateral dynamics at different speeds using nonlinear methods. The aim is to investigate the velocity dependence of the dynamics.

Open Access: Yes

DOI: 10.3390/engproc2024079053

Hammerstein Model Identification for Autonomous Vehicle Dynamics by Two-Stage Algorithm †

György Terdik Dániel Pup György Istenes J. Bokor

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this paper, the nonlinear identification (ID) of the lateral dynamics of a road vehicle is presented. The mathematical description of lateral dynamics is crucial for developing various self-driving functions. One method of describing dynamics is system identification from measured data. During the measurements, the steering servo of a test vehicle kept in straight-line motion by a self-driving function was artificially excited. A Hammerstein–Wiener model was successfully applied for the identification of these measurements. A nonlinear estimator was used during the fitting, which needed high computing power. For the Hammerstein–Wiener model, we used the two-stage algorithm (TSA) with a bilinear estimation method, which makes it possible to apply linear regression. We compared these methods during simulations and real data.

Open Access: Yes

DOI: 10.3390/engproc2024079054

Fuzzy Decision Support Methodology for Sustainable Packaging System Design

A. Buruzs Dániel Pup Kata Vöröskoi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: 163-173

Description:

The aim of the present paper is to develop an integrated method that provides assistance to decision makers during packaging system planning, design, operation and evaluation from an environmental perspective. The role of the packaging system is to provide a cover for the handling and communication functions surrounding the product. Single-use and reusable packaging are known based on the time it participates in the goods trade. The purpose of the authors is to develop an evaluation model for the selection of packaging systems from an environmental and sustainability point of view in the supply chain.

Open Access: Yes

DOI: 10.1007/978-3-030-88817-6_19

Data-driven linear parameter-varying modelling of the steering dynamics of an autonomous car

Gabor Rodonyi R. Tóth Peter Koros Dániel Pup Ádám Kisari Zsombor Vigh J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 8

Page Range: 20-26

Description:

Developing automatic driving solutions and driver support systems requires accurate vehicle specific models to describe and predict the associated motion dynamics of the vehicle. Despite of the mature understanding of ideal vehicle dynamics, which are inherently nonlinear, modern cars are equipped with a wide array of digital and mechatronic components that are difficult to model. Furthermore, due to manufacturing, each car has its personal motion characteristics which change over time. Hence, it is important to develop data-driven modelling methods that are capable to capture from data all relevant aspects of vehicle dynamics in a model that is directly utilisable for control. In this paper, we show how Linear Parameter-Varying (LPV) modelling and system identification can be applied to reliably capture personalised model of the steering system of an autonomous car based on measured data. Compared to other nonlinear identification techniques, the obtained LPV model is directly utilisable for powerful controller synthesis methods of the LPV framework.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.575

Identification of the nonlinear steering dynamics of an autonomous vehicle

Gabor Rodonyi R. Tóth M. Schoukens Peter Koros Dániel Pup Ádám Kisari G. I. Beintema Zsombor Vigh Alexandros Soumelidis J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 7

Page Range: 708-713

Description:

Automated driving applications require accurate vehicle specific models to precisely predict and control the motion dynamics. However, modern vehicles have a wide array of digital and mechatronic components that are difficult to model, manufactures do not disclose all details required for modelling and even existing models of subcomponents require coefficient estimation to match the specific characteristics of each vehicle and their change over time. Hence, it is attractive to use data-driven modelling to capture the relevant vehicle dynamics and synthesise model-based control solutions. In this paper, we address identification of the steering system of an autonomous car based on measured data. We show that the underlying dynamics are highly nonlinear and challenging to be captured, necessitating the use of data-driven methods that fuse the approximation capabilities of learning and the efficiency of dynamic system identification. We demonstrate that such a neural network based subspace-encoder method can successfully capture the underlying dynamics while other methods fall short to provide reliable results.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.444

Alternative Propulsion Buses in the Metropolitan Public Transport

István Lakatos Dániel Pup Andor Nagy Ferenc Szauter

Publication Name: Lecture Notes in Mechanical Engineering

Publication Date: 2021-01-01

Volume: 22

Issue: Unknown

Page Range: 49-66

Description:

The lecture is analysing the possibility of an optimal energy mix through the example of a Hungarian metropolis. Using the city bus routes, we analyse and compare the traditional Diesel, CNG, and electric propulsion. An optimal energy mix is provided by using SWOT analysis.

Open Access: Yes

DOI: 10.1007/978-981-15-9529-5_5

Characterization of Model Uncertainty Features Relevant to Model Predictive Control of Lateral Vehicle Dynamics

Gabor Rodonyi Dániel Pup Ádám Kisari Zsombor Vigh Alexandros Soumelidis J. Bokor

Publication Name: 2020 23rd IEEE International Symposium on Measurement and Control in Robotics Ismcr 2020

Publication Date: 2020-10-15

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The information about a system's dynamics represented by measurement data sets are often confined to regions of restricted operations where the system is not sufficiently excited for model identification purposes. Experiments performed in closed-loop with safety constraints allow only for reduced order modeling. In the paper, a set of low order models are identified from real experimental data of the lateral dynamics of an electric passenger car. Low order models are advantageous for on-line computation in model-based control, though uncertainty due to neglected dynamics may deteriorate control performance and constraint satisfaction. The effect of uncertainty is analyzed by controller cross-validation where a controller designed based on one model is evaluated on other models playing the role of the true system. This method allows us to qualify not only model-controller pairs, but to determine the properties of input data and model uncertainty, which lead to more useful data sets, more robust and better performing controllers than the others.

Open Access: Yes

DOI: 10.1109/ISMCR51255.2020.9263745

Experimental verification of a control system for autonomous navigation

Gabor Rodonyi Peter Koros Dániel Pup Ádám Kisari Benedek Szucs Alexandros Soumelidis J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2020-01-01

Volume: 53

Issue: 2

Page Range: 14273-14278

Description:

A flexible architecture is developed with the purpose of supporting education and research on the field of autonomous vehicles. A pure electric vehicle is equipped with on-board computational units, sensors and actuator interfaces. This paper presents the current status of the control system and its validation by means of navigation experiments. With the cascade control architecture, problems of actuator dead-zone, sensor offset errors, path tracking and redesign for obstacle avoidance are addressed.

Open Access: Yes

DOI: 10.1016/j.ifacol.2020.12.1171

Robustness analysis and reconfiguration strategy of autonomous vehicles in intersections

Balazs Nemeth Dániel Pup Péter Gáspár Peter Szilassy Ferenc Szauter

Publication Name: Saci 2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2019-05-01

Volume: Unknown

Issue: Unknown

Page Range: 45-50

Description:

The paper proposes the design of a neural-network-based control strategy of autonomous vehicles in intersections. The motivation of the neural network approach is to reduce the numerically-intensive computation of the optimization problem in which the motions of autonomous vehicles are formed. In the method the neural network is trained through a preliminary optimal off-line solution. Moreover, a robustness analysis and a reconfiguration strategy for the scenarios with vehicle position disturbances are proposed. The design and the analysis are illustrated through CarSim simulation examples.

Open Access: Yes

DOI: 10.1109/SACI46893.2019.9111527

Study on a road surface estimation method based on big data analysis

Balazs Nemeth Dániel Pup Daniel Fenyes Péter Gáspár Ferenc Szauter

Publication Name: Saci 2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2019-05-01

Volume: Unknown

Issue: Unknown

Page Range: 57-62

Description:

The paper presents a new method to classify the road surfaces according to the adhesion coefficient between the tire and road surface using big data approach. In this research, three different categories of the road surface are considered, such as dry, wet and icy. The purpose of classification is to create a model, which is able to determine the type of the actual road surface using only the measured data of the vehicle. The classification method is, basically, based on the C4.5 decision tree algorithm, while the data is provided the high-fidelity simulation software, CarSim. Finally, the efficiency of the resulted model is demonstrated through a complex simulation.

Open Access: Yes

DOI: 10.1109/SACI46893.2019.9111487

Research of vehicle parameter and sensor systems necessary to control autonomous vehicles

Dániel Pup Gábor Szakállas József Polák

Publication Name: 2018 14th IEEE ASME International Conference on Mechatronic and Embedded Systems and Applications Mesa 2018

Publication Date: 2018-08-27

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Our long-term goal is to implement autonomous vehicle control functions on a standard vehicle. At first we started with the investigation of the steering, which is a crucial area of the control of autonomous vehicles. As a part of the program, vehicle dynamical measurements were carried out on a Nissan Leaf electric vehicle equipped with a sensor system.

Open Access: Yes

DOI: 10.1109/MESA.2018.8449146

Research of required vehicle system parameters and sensor systems for autonomous vehicle control

András Mihály Peter Koros Dániel Pup Huba Somogyi Alexandros Soumelidis

Publication Name: Saci 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2018-08-20

Volume: Unknown

Issue: Unknown

Page Range: 27-32

Description:

Our long-term goal is to implement autonomous vehicle control functions on a standard vehicle. At first we started with the investigation of the steering, which is a crucial area of the control of autonomous vehicles. As a part of the program, vehicle dynamical measurements were carried out on a Nissan Leaf electric vehicle equipped with a sensor system, furthermore we design a high-level trajectory-tracking controller.

Open Access: Yes

DOI: 10.1109/SACI.2018.8441008

Structure Selection and LPV Model Identification of a Car Steering Dynamics⁎

Gabor Rodonyi Zoltán Szabó Peter Koros Dániel Pup Alexandros Soumelidis J. Bokor

Publication Name: Unknown

Publication Date: 2018-01-01

Volume: 51

Issue: 15

Page Range: 1086-1091

Description:

A Linear Parameter-Varying (LPV), discrete-time black box model of an electric power assisted steering system of a passenger car is identified from open-loop step response measurement data. The goal is to provide a nominal model for control design and analysis that is able to describe the principal characteristics of the system in the whole region of steering angle and speed range of 3 to 30 km/h. Examining a set of experimental data by using classical linear time-invariant black box modeling and validation techniques, the structure of the LPV model is determined. The parameters of the model are identified based on minimizing a quadratic error criterion by nonlinear optimization algorithms.

Open Access: Yes

DOI: 10.1016/j.ifacol.2018.09.049

Complex analysis of vehicle and environment dynamics

István Lakatos Dániel Pup Tamas Péter Ferenc Szauter

Publication Name: Mesa 2016 12th IEEE ASME International Conference on Mechatronic and Embedded Systems and Applications Conference Proceedings

Publication Date: 2016-10-07

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper introduces mathematical modelling, the development of diagnostic methods and the design of producing a prototype. Its aim is to establish a new, accredited research laboratory for the testing and quality assurance of hybrid and electric driven vehicles. The task is very complex and it puts special emphasis on environmental and safety issues. It highlights the fact that its application under laboratory conditions establishes a new situation for measurement. It points out that the complex research which develops diagnostic techniques and procedures related to real operation and urban environment, moreover, applies optimal planning methods still has novelty.

Open Access: Yes

DOI: 10.1109/MESA.2016.7587112

An in-depth analysis of cycling and pedestrian accidents in Hungary

József Óberling István Lakatos Dániel Pup Tamas Péter Ferenc Szauter

Publication Name: Mesa 2016 12th IEEE ASME International Conference on Mechatronic and Embedded Systems and Applications Conference Proceedings

Publication Date: 2016-10-07

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The National Committee for Accident Prevention (OBB) of the National Police Headquarters of Hungary (ORFK) has ordered an analytical research on accidents involving cyclists and pedestrians in 2013-14. The Department of Automotive and Railway Engineering at Széchenyi István University Gyor has carried out an evaluative and analytical study on this issue and has made proposals based on the results of the study. Within the framework of this project, it has also set out actions aiming to increase road safety. The following study gives an insight into this analysis.

Open Access: Yes

DOI: 10.1109/MESA.2016.7587113

Determination of power and torque curves of electric driven vehicles based on diagnostic methods

István Lakatos Dávid Czeglédi Dániel Pup

Publication Name: Proceedings of the ASME Design Engineering Technical Conference

Publication Date: 2015-01-01

Volume: 9

Issue: Unknown

Page Range: Unknown

Description:

The transmitted power of motors can be defined by test bench examinations, in which the motor needs to be dismounted. By applying diagnostic methods only minimal disassembly, or indeed none at all, is necessary. In this paper diagnostic methods are systematized by different studies. Moreover, a new diagnostic procedure (established by the authors) is also introduced, which can be carried out by a relatively cheap measuring system design. Power measurement on a roller test bench is a well-Tried technique for vehicle examination. Basically, the wheel parameters (tractive force, torque, power) are measured, but there are also procedures for motor power measurement. By applying the new procedure, the diagnostic method, (simple construction and test bench construction at a favourable price) torque and power characteristics of the mounted motor can be defined. The theoretical considerations of the new measuring technique and the implementation of the measuring system are introduced in this paper. Test bench for drive motor power and torque curve determination. In this study the diagnostical measuring systems and, for the first time, the measuring principle and technology of the new theorybased roller power test bench are presented. For its construction measurements have been carried out which make an important contribution to the research. The results of the research contribute to the development of diagnostics methods and to making them more wide-spread.

Open Access: Yes

DOI: 10.1115/DETC2015-46724