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

Rafał Doniec; Natalia Piaseczna; Frédéric Li; Konrad Duraj; Hawzhin Hozhabr Pour; Marcin Grzegorzek; Katarzyna Mocny-Pachońska; Ewaryst Tkacz

doi:10.3390/electronics11182960

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

Rafał Doniec, Natalia Piaseczna^*, Frédéric Li, Konrad Duraj, Hawzhin Hozhabr Pour, Marcin Grzegorzek, Katarzyna Mocny-Pachońska, Ewaryst Tkacz

^*Corresponding author for this work

Abstract

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.

Original language	English
Article number	2960
Journal	Electronics (Switzerland)
Volume	11
Issue number	18
DOIs	https://doi.org/10.3390/electronics11182960
Publication status	Published - 09.2022

Research Areas and Centers

Centers: Center for Artificial Intelligence Luebeck (ZKIL)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/electronics11182960

Cite this

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

abstract = "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.",

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T1 - Classification of Roads and Types of Public Roads Using EOG Smart Glasses and an Algorithm Based on Machine Learning While Driving a Car

AU - Doniec, Rafał

AU - Piaseczna, Natalia

AU - Li, Frédéric

AU - Duraj, Konrad

AU - Pour, Hawzhin Hozhabr

AU - Grzegorzek, Marcin

AU - Mocny-Pachońska, Katarzyna

AU - Tkacz, Ewaryst

PY - 2022/9

Y1 - 2022/9

N2 - 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.

AB - 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.

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

Abstract

Research Areas and Centers

UN SDGs

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