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스마트워치를 이용한 자동차운전자 구분 및 핸들의 회전 방향 인지 기법

A Method for Driver Recognition and Steering Wheel Turning Direction Estimation Using Smartwatches

  • 투고 : 2019.09.04
  • 심사 : 2019.09.24
  • 발행 : 2019.09.30

초록

웨어러블 디바이스의 대중화에 따라 디바이스 내에 탑재된 다양한 센서를 활용하여 동작 인식, 헬스케어, 안전 보조 등 다양한 스마트 서비스를 제공하는 애플리케이션이 급증하고 있다. 본 논문에서는 9축 관성 센서가 탑재된 스마트워치를 이용하여 운전자를 인식하고, 운전 중 운전자의 자동차 핸들의 회전각을 탐지하는 방법을 제안한다. 제안하는 시스템은 i) 스마트워치 위치 인식, ii) 운전자 인식, iii) 핸들의 회전각 계산, 3가지 단계로 구성되어 있다. 이를 위해, IMU 센서와 아두이노(Arduino)를 이용하여 웨어러블 디바이스의 시제품을 자체 제작하고 제안하는 시스템을 구현 하였다. 실험을 통해 핸들의 회전 방향을 높은 정확도로 계산할 수 있고 회전각 또한 평균 $11.77^{\circ}$의 낮은 오차를 보여 제안하는 시스템의 실효성을 입증하였다.

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

키워드

참고문헌

  1. B. Y. Jung, "Current Status and Prospects of the Wearable Devices Market," KISDI Research Report, vol.30, no.20, pp.1-7, 2018.
  2. H. Huang, H. Chen, S. Lin, "MagTrack: Enabling Safe Driving Monitoring with Wearable Magnetics," in Proc. of the 17th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys'19), pp.316-339, 2019. DOI: 10.1145/3307334.3326107
  3. C. Bi, J. Huang, G. Xing, L. Jiang, X. Liu, M. Chen, "SafeWatch: AWearable Hand Motion Tracking System for Improving Driving Safety," in Proc. of the Second International Conference on Internet-of-Things Design and Implementation (IoTDI '17). ACM, pp.223-232, 2017. DOI: 10.1145/3054977.3054979
  4. A. Parate, et al. "RisQ: Recognizing smoking gestures with inertial sensors on a wristband," in Proc. of the 12th annual international conference on Mobile systems, applications, and services (Mobisys'14), pp.149-161, 2014. DOI:10.1145/2594368.2594379
  5. D. Chen, et al. "Invisible sensing of vehicle steering with smartphones," in Proc. of the 13th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys'15), pp.1-13, 2015. DOI: 10.1145/2742647.2742659
  6. Steffen, Rainer, et al. "Near field communication (NFC) in an automotive environment," in Proc. of the 2nd International Workshop on Near Field Communication. IEEE, 2010. DOI: 0.1109/NFC.2010.11
  7. J. Yang, et al. "Detecting driver phone use leveraging car speakers," in Proc. of the 17th annual international conference on Mobile computing and networking (Mobisys'11), pp.97-108, 2011. DOI:10.1145/2030613.2030625
  8. H. Park, et al. "Poster: Are you driving?: non-intrusive driver detection using built-in smartphone sensors," in Proc. of the 20th annual international conference on Mobile computing and networking, 2014. DOI: 10.1145/2639108.2642896
  9. C. Bo, X. Jian, X. Li, X. Mao, Y. Wang, F. Li, "You're driving and texting: detecting drivers using personal smart phones by leveraging inertial sensors," in Proc. of the 19th annual international conference on Mobile computing & networking (ACM Mobicom 13), pp.199-202, 2013. DOI: 10.1145/2500423.2504575
  10. H. Chu, et al. "I am a smartphone and I know my user is driving," IEEE in Proc. of the Communication Systems and Networks, 2014. DOI :10.1109/COMSNETS.2014.6734870
  11. R. Araujo, et al, "Driving coach: A smartphone application to evaluate driving efficient patterns," in Proc. of the IEEE Intelligent Vehicles Symposium (IV), 2012. DOI: 10.1109/IVS.2012.6232304
  12. K. Li, F. Lu, Q. Lv, L. Shang, D. Maksimovic, "Personalized driving behavior monitoring and analysis for emerging hybrid vehicles," Pervasive Computing. Springer Berlin Heidelberg, vol.7319, pp.1-19, 2012. DOI: 10.1007/978-3-642-31205-2_1