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  -