Toward Collecting Driving Data Using Wrist-Worn Sensors in Real Vehicles and its Application to Driver Activity Recognition

• Published in: Journal of Japan Society for Fuzzy Theory and Intelligent Informatics Vol. 37; no. 1; pp. 544 - 548
• Main Authors: OKUYAMA, Toshihiro, ARAKAWA, Toshiya, AKIDUKI, Takuma, KAWAHARA, Tomohiro, TAKAHASHI, Hirotaka
• Format: Journal Article
• Language: Japanese
• Published: Iizuka Japan Society for Fuzzy Theory and Intelligent Informatics 15.02.2025; 日本知能情報ファジィ学会; Japan Science and Technology Agency
• Subjects: Activity recognition; Data collection; driver activity recognition; driver status monitoring; Driving; hand acceleration; Human factors; Sensors; State estimation; Traffic accidents; wearable sensor; Wrist; ウェアラブルセンサ; ドライバモニタリング; ドライバ行動推定; 手先加速度
• ISSN: 1347-7986; 1881-7203; 1881-7203
• DOI: 10.3156/jsoft.37.1_544

To prevent traffic accidents caused by human factors, it is essential to identify the potential risk factors in daily driving. To address this challenge, a low-cost and easy-to-use method is required to continuously collect and measure the driver’s state information while protecting the driver’s privacy. To address this issue, we have developed a driver state estimation method using wrist-worn sensors. However, the verification of our approach has been limited to laboratory environments thus far. Therefore, in this study, we developed an in-vehicle measurement system using wrist-worn sensors and conducted experiments to collect driving behavior data in a real-world environment. We then estimated the driver’s behavior from the collected hand acceleration data. From the results, we identified challenges in applying our method to real-world conditions. Finally, based on these approaches, we developed a framework for collecting data in real-world environments and constructing datasets.