Lovas, Tamás and Ormándi, Tamás and Somogyi, József Árpád and Baranyai, Dániel and Tihanyi, Viktor Roland and Tettamanti, Tamás (2022) OpenCRG models from different data sources to support vehicle simulations. IEEE ACCESS, 10. pp. 42690-42698. ISSN 2169-3536 10.1109/ACCESS.2022.3168287

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Abstract

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.

Item Type:	Article
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Systems and Control Lab
SWORD Depositor:	MTMT Injector
Depositing User:	MTMT Injector
Date Deposited:	16 Feb 2023 07:43
Last Modified:	11 Sep 2023 15:00
URI:	https://eprints.sztaki.hu/id/eprint/10500

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