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- Title
Driving Reality vs. Simulator: Data Distinctions.
- Authors
Piaseczna, Natalia; Doniec, Rafał; Sieciński, Szymon; Barańska, Klaudia; Jędrychowski, Marek; Grzegorzek, Marcin
- Abstract
As the automotive industry undergoes a phase of rapid transformation driven by technological advancements, the integration of driving simulators stands out as an important tool for research and development. The usage of such simulators offers a controlled environment for studying driver behavior; the alignment of data, however, remains a complex aspect that warrants a thorough investigation. This research investigates driver state classification using a dataset obtained from real-road and simulated conditions, recorded through JINS MEME ES_R smart glasses. The dataset encompasses electrooculography signals, with a focus on standardizing and processing the data for subsequent analysis. For this purpose, we used a recurrent neural network model, which yielded a high accuracy on the testing dataset (86.5%). The findings of this study indicate that the proposed methodology could be used in real scenarios and that it could be used for the development of intelligent transportation systems and driver monitoring technology.
- Subjects
ARTIFICIAL neural networks; RECURRENT neural networks; BIOMEDICAL signal processing; TECHNOLOGICAL innovations; AUTOMOBILE driving simulators; INTELLIGENT transportation systems; MEMES
- Publication
Electronics (2079-9292), 2024, Vol 13, Issue 14, p2708
- ISSN
2079-9292
- Publication type
Article
- DOI
10.3390/electronics13142708