TY - JOUR AU - Dowajy, Mohammad AU - Somogyi, József Árpád AU - Barsi, Árpád AU - Lovas, Tamás TI - An Automatic Road Surface Segmentation in Non-Urban Environments: A 3D Point Cloud Approach with Grid Structure and Shallow Neural Networks JF - IEEE ACCESS J2 - IEEE ACCESS VL - 12 PY - 2024 SP - 33035 EP - 33044 PG - 10 SN - 2169-3536 DO - 10.1109/ACCESS.2024.3372431 UR - https://m2.mtmt.hu/api/publication/34742506 ID - 34742506 N1 - Export Date: 18 March 2024 AB - Automatic road segmentation from three-dimensional point cloud data has gained increasing interest recently. However, it is still challenging to do this task automatically due to the wide variations of roads and complex environments, especially in non-urban areas. This research proposed a comprehensive approach for using shallow neural networks to segment non-urban road point clouds to support autonomous driving applications. The proposed approach involves converting raw point cloud data into a regular grid of cells or partial clouds. Initially, a shallow neural network based on cells’ properties (cell plane fitting error, cell average intensity, cell elevation range, and cell weighted density) was employed to extract road cells from raw point cloud data. The road cells were refined and segmented into inside-road and road border point clouds based on morphologic operations. A point-wise shallow neural network was used to extract road points from the border point clouds based on intensity and geometric features (roughness, curvature, and change rate of the normal). A precise road surface point cloud is obtained by merging the inside-road and filtered border point clouds. The method performance was evaluated for two datasets captured using a mobile laser scanner (MLS). In the first dataset, the road points were extracted at average completeness, correctness, quality, and overall accuracy of 98.40%, 99.13%, 97.56%, and 98.47%, respectively. Similarly, the method achieved high scores for the second dataset with 97.22% completeness, 99.02% correctness, 96.29% quality, and 98.71% overall accuracy. The method performance demonstrates an advancement when compared to various state-of-the-art methods and also confirms its adaptability to different road environments. Authors LA - English DB - MTMT ER - TY - CHAP AU - Somogyi, József Árpád AU - Tettamanti, Tamás AU - Varga, Pál AU - Szalay, Zsolt AU - Baranyai, Dániel AU - Lovas, Tamás ED - Akkaya, K ED - Festor, O ED - Fung, C ED - Rahman, M A ED - Granville, L Z ED - dos Santos, C R A TI - Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements T2 - NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium PB - IEEE CY - Piscataway (NJ) SN - 9781665477161 PY - 2023 SP - 1 EP - 6 PG - 6 DO - 10.1109/NOMS56928.2023.10154403 UR - https://m2.mtmt.hu/api/publication/34033754 ID - 34033754 N1 - Budapest University of Technology and Economics, Fac. of Civil Engineering, Dept. of Photogrammetry and Geoinformatics, Budapest, Hungary Institute for Computer Science and Control, The Eötvös Loránd Research Network, Systems and Control Laboratory, Budapest, Hungary Budapest University of Technology and Economics, Fac. of Electrical Engineering and Informatics, Dept. of Telecommunications and Media Informatics, Budapest, Hungary Budapest University of Technology and Economics, Fac. of Transportation Eng. and Vehicle Eng., Dept. of Automotive Technologies, Budapest, Hungary Export Date: 27 July 2023 Correspondence Address: Somogyi, A.; Budapest University of Technology and Economics, Hungary LA - English DB - MTMT ER - TY - JOUR AU - Dowajy, Mohammad AU - Baranyai, Dániel AU - Somogyi, József Árpád AU - Vrbovszki, Robert AU - Lovas, Tamás TI - Comparative analysis of Road Scanning Techniques JF - NOVA GEODESIA J2 - NOVA GEODESIA VL - 3 PY - 2023 IS - 1 SP - 111 SN - 2810-2754 DO - 10.55779/ng31111 UR - https://m2.mtmt.hu/api/publication/33701095 ID - 33701095 AB - A three-dimensional road point cloud is not only useful for civil engineers (road rehabilitation, road condition assessment) but can also be useful for vehicle engineers (autonomous vehicle driving scenario, vehicle dynamics simulation). Currently, there are several scanning techniques can be used to obtain these point clouds, such as terrestrial laser scanning (TLS), mobile laser scanning (MLS), airborne laser scanning (ALS), unmanned aerial vehicle (UAV) photogrammetry or UAV laser scanning. This paper discusses the investigation of four road surface scanning techniques by comparing their point clouds and the derived products. The comparison was performed for a section of a road with 1136 m length and 4 m width, the TLS survey provided the reference data. Aspects of point cloud evaluation included geometric accuracy, density, and the parameters of plane-fitting. CRG models were created from all studied point clouds to compare the difference between the final products to be used by the automotive industry. The results show that the MLS and the UAV photogrammetry generated the most accurate point cloud, while UAV laser scanning accuracy was the lowest. Similarly, the CRG models comparison showed that there was no significant difference between MLS and TLS models, and the UAV photogrammetry gave a smoother variation relative to the reference surface. Whereas the largest differences were noted for the CRG model derived from the UAV laser scanning models. LA - English DB - MTMT ER - TY - JOUR AU - Somogyi, József Árpád AU - SZABO-LEONE, Akos AU - Lovas, Tamás TI - Testing the measurability of steel sections with terrestrial laser scanners JF - NOVA GEODESIA J2 - NOVA GEODESIA VL - 2 PY - 2022 IS - 4 SP - 66 SN - 2810-2754 DO - 10.55779/ng2466 UR - https://m2.mtmt.hu/api/publication/33535817 ID - 33535817 AB - When assessing the health of steel structures, capturing, and modelling the geometry is especially important. Point cloud-based technologies have special requirements; previous studies revealed certain challenges that are to be resolved. In this paper, we aimed to develop a method to investigate the effects that the surface reflectance, incidence angle, and distance have on the quality of the point cloud of steel sections. A controlled environment was established for the research, where three terrestrial laser scanners were used to measure four different steel specimens. For validation, we also made reference measurements with a structured light scanner. Due to a large amount of data, a workflow with own routines has been developed for processing the prepared measurement datasets. For standard steel sections, the comparative study clearly showed a significant influence of the section shape, resulting in occlusion and unfavorable incidence angles. Of the devices tested, the one de-signed for high-precision measurements showed the intensity highlighting phenomenon for highly reflective surfaces, however, the measurements demonstrate that with careful selection of measurement conditions and a few pre-processing steps, the technology is well suited for the assessment of steel structures. LA - English DB - MTMT ER - TY - JOUR AU - Somogyi, József Árpád AU - Lovas, Tamás AU - Szabó-Leone, Ákos AU - Fehér, András TI - Steels Specimens’ Inspection with Structured Light Scanner JF - PERIODICA POLYTECHNICA-CIVIL ENGINEERING J2 - PERIOD POLYTECH CIV ENG VL - 66 PY - 2022 IS - 4 SP - 1241 EP - 1247 PG - 7 SN - 0553-6626 DO - 10.3311/PPci.20081 UR - https://m2.mtmt.hu/api/publication/33105263 ID - 33105263 N1 - Department of Photogrammetry and Geoinformatics, Faculty of Civil Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary 4iG Plc, Montevideo u. 8., Budapest, H-1037, Hungary Export Date: 18 October 2022 Correspondence Address: Somogyi, Á.J.; Department of Photogrammetry and Geoinformatics, Műegyetem rkp. 3., Hungary; email: somogyi.arpad@emk.bme.hu Funding Agency and Grant Number: [2017-1.3.1-VKE-2017-00040 (2018-2021)] Funding text: Acknowledgement The research reported in this paper was supported by BOSS5D project under grant agreement No. 2017-1.3.1-VKE-2017-00040 (2018-2021) . Application of networking technologies in the field of design, manufacturing, assem-bly, maintenance, and related services of steel structures. AB - With the recent rapid advances in technology, the use of 3D scanning systems in the engineering world has become more and more prevalent thanks to the ease of use, the improved data collection process, and the increase in the accuracy of the acquired data. During the rebuilding of the Tisza bridge on the M4 motorway, the contractor discovered that the plates used to build the steel superstructure had developed corrosion damage during several years of storage. Plates with a tolerable level of corrosion were intended to be used, but the question was how the increased surface roughness will affect the fatigue life of the plates and the welded steel fabrications made from the plates. As part of this test, fatigue specimens were measured from the material to be used for the bridge and welded with two different geometries with the help of a structured light 3D scanner (SLS scanner). This paper discusses the measurement and inspection of these steel specimens of a highway bridge, before and after the fatigue test of the parts. From the acquired data we examined defects on the surface of the parts, physical deformations by comparing measured data to a CAD model and calculated the amount of material which was lost during stress testing. LA - English DB - MTMT ER - TY - JOUR AU - Somogyi, József Árpád AU - Tar, László AU - Vári, Barnabás AU - Fehér, András TI - Monostori híd építésének életútkövetése JF - MAGÉSZ ACÉLSZERKEZETEK J2 - MAGÉSZ ACÉLSZERKEZETEK VL - 19 PY - 2022 IS - 2 SP - 28 SN - 1785-4822 UR - https://m2.mtmt.hu/api/publication/32863488 ID - 32863488 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Somogyi, József Árpád AU - Tar, László AU - Fehér, András TI - Kövesgyűri gyártócsarnok lézerszkenneres mérése JF - MAGÉSZ ACÉLSZERKEZETEK J2 - MAGÉSZ ACÉLSZERKEZETEK VL - 19 PY - 2022 IS - 2 SP - 73 SN - 1785-4822 UR - https://m2.mtmt.hu/api/publication/32863476 ID - 32863476 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Völgyi, István Krisztián AU - Joó, Attila László AU - Hegyi, Péter AU - Kollár, Dénes AU - Somogyi, József Árpád TI - A Monostori híd mérőrendszere gyártástól a monitoring rendszerig JF - MAGÉSZ ACÉLSZERKEZETEK J2 - MAGÉSZ ACÉLSZERKEZETEK VL - 19 PY - 2022 IS - különszám SP - 20 EP - 27 PG - 8 SN - 1785-4822 UR - https://m2.mtmt.hu/api/publication/32862943 ID - 32862943 LA - Hungarian DB - MTMT ER - TY - BOOK AU - Lovas, Tamás AU - Baranyai, Dániel AU - Somogyi, József Árpád TI - Point Cloud Based Road Surface Modelling and Assessment PY - 2022 SP - 4 DO - 10.3311/BMEZalaZONE2022-015 UR - https://m2.mtmt.hu/api/publication/32820034 ID - 32820034 LA - English DB - MTMT ER - TY - JOUR AU - Lovas, Tamás AU - Ormándi, Tamás AU - Somogyi, József Árpád AU - Baranyai, Dániel AU - Tihanyi, Viktor Roland AU - Tettamanti, Tamás TI - OpenCRG models from different data sources to support vehicle simulations JF - IEEE ACCESS J2 - IEEE ACCESS VL - 10 PY - 2022 SP - 42690 EP - 42698 PG - 9 SN - 2169-3536 DO - 10.1109/ACCESS.2022.3168287 UR - https://m2.mtmt.hu/api/publication/32791236 ID - 32791236 N1 - Funding Agency and Grant Number: National Research Development and Innovation Fund [TKP2020] Funding text: The research reported in this paper and carried out at the Budapest University of Technology and Economics has been supported by the National Research Development and Innovation Fund (TKP2020 National Challenges Subprogram, Grant No. BME-NC) based on the charter of bolster issued by the National Research Development and Innovation Ofce under the auspices of the Ministry for Innovation and Technology. AB - Digital twins of road surfaces support multiple engineering applications. Remote sensing technologies provide information from the entire surface of the pavement by high accuracy point clouds. Pavement errors and differences from designed geometry can be detected and assessed using such datasets, while OpenCRG models derived from point clouds support transportation applications. High-resolution CRG (Curved Regular Grid) models enable analyzing vehicle suspension systems in vehicle dynamics simulation environments. Furthermore, such models also support creating the digital twins of vehicle suspensions and improve the development and research of models related to vehicle dynamics. The paper presents how the suspension digital twin was obtained applying a genetic algorithm and how it was assessed. The quality of raw data and that of the derived methods are analyzed in the case of multiple mapping technologies (terrestrial, mobile, and aerial laser scanning). CRG models were created from all datasets, and their applicability was investigated to support vehicle simulations with high accuracy demand. Other important vehicle-related use cases are also mentioned in the paper. LA - English DB - MTMT ER -