Classification of Roads and Types of Public Roads Using EOG Smart Glasses and an Algorithm Based on Machine Learning While Driving a Car

Driving a car is an activity that became necessary for exploration, even when living in the present world. Research exploring the topic of safety on the roads has therefore become increasingly relevant. In this paper, we propose a recognition algorithm based on physiological signals acquired from JI...

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Bibliographic Details
Published in:Electronics (Basel) 2022-09, Vol.11 (18), p.2960
Main Authors: Doniec, Rafał, Piaseczna, Natalia, Li, Frédéric, Duraj, Konrad, Pour, Hawzhin Hozhabr, Grzegorzek, Marcin, Mocny-Pachońska, Katarzyna, Tkacz, Ewaryst
Format: Article
Language:English
Subjects:
Acceleration
Accident prevention
Algorithms
Angular velocity
Artificial intelligence
Augmented Reality
Automobile driving
Automobile sales
Classification
Datasets
Driver behavior
Driving conditions
Feature extraction
Identification and classification
Machine learning
Motor ability
Physiology
Poland
Public transportation
Roads
Roads & highways
Sensors
Streets
Traffic
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Summary:Driving a car is an activity that became necessary for exploration, even when living in the present world. Research exploring the topic of safety on the roads has therefore become increasingly relevant. In this paper, we propose a recognition algorithm based on physiological signals acquired from JINS MEME ES_R smart glasses (electrooculography, acceleration and angular velocity) to classify four commonly encountered road types: city road, highway, housing estate and undeveloped area. Data from 30 drivers were acquired in real driving conditions. Hand-crafted statistical features were extracted from the physiological signals to train and evaluate a random forest classifier. We achieved an overall accuracy, precision, recall and F1 score of 87.64%, 86.30%, 88.12% and 87.08% on the test dataset, respectively.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics11182960