한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
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OBD-II 정보를 이용한 운전자 스트레스 모니터링 시스템

Driving Stress Monitoring System Based on Information Provided by On-Board Diagnostics Version II

  • 조상진 ((주)지메이드 ) ;
  • 조영 (울산과학대학교 전기전자공학부)
  • 투고 : 2022.12.23
  • 심사 : 2023.02.17
  • 발행 : 2023.02.28
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초록

인간의 생체 신호 데이터가 인간의 상태를 가장 잘 설명할 수 있다 할지라도 실제 운전 중에 운전자의 생체 데이터를 얻어 운전자의 상태를 판단하는 일은 쉽지 않다. 본 논문에서는 이러한 한계를 극복하기 위한 방법 중 하나로 운전자의 주행 정보를 이용한 운전자 스트레스 모니터링 시스템을 제안한다. 운전자의 주행 정보는 OBD-II 스캐너를 통해 취득하고, 실제 운전자의 운전 스트레스 여부는 E4 밴드를 통해 취득한 EDA 데이터를 이용하여 판단한다. 스트레스 감지 모델은 MLP 신경망 모델을 사용하였으며 약 한 달 간의 운행 데이터를 이용하여 학습시켰다. 제안한 시스템을 평가하기 위하여 약 1시간의 운행 데이터를 사용하였고 약 92%의 정확도를 얻을 수 있었다.

Although the biosignal is the best way to represent the human condition, it is difficult to acquire the biosignal of a driver driving for detecting driver's condition. As one of the methods to overcome this limitation, this paper proposes a driving stress monitoring system based on information provided by OBD-II(on-board diagnostics version II). The driving information and EDA(Electrodermal activity) data are obtained through the OBD-II scanner and E4 wristband, respectively. EDA data is used as ground truth to distinguish whether driver is stressed or not. MLP(multi-layer perceptron) neural network is used as a model to detect driving stress and is trained using driving data for about a month. To evaluate the proposed system, we used about 1 hour of driving data and the accuracy is 92%.

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참고문헌

  1. J.-H. Son, H.-Y. Lee, H.-J. Bae, Y.-H. Kim, and B.-J. Lee, "Driving under influence Prevention System Using Fingerprint sensors with Arduino," J. of the Korea Institute of Electronics Communications Sciences, vol. 17, no. 5, 2022, pp. 969-976. 
  2. H.-M. Lee, W.-W. Lee, and J.-A. Jang, "Quantification Method of Driver's Dangerous Driving Behavior Considering Continuous Driving Time," J. of the Korea Institute of Electronics Communications Sciences, vol. 17, no. 4, 2022, pp. 723-728. 
  3. Y.-H. Kong, H.-J. Kim, Y.-J. Yi, and S.-J. Kang, "Development of Incident Detection Algorithm using GPS Data," J. of the Korea Institute of Electronics Communications Sciences, vol. 16, no. 4, 2021, pp. 771-782. 
  4. A. Tjolleng, K. Jung, W. Hong, W. Lee, B. Lee, H. You, J. Son, and S. Park, "Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals," Applied Ergonomics, vol. 59, part A, 2017, pp. 326-332.  https://doi.org/10.1016/j.apergo.2016.09.013
  5. S. Lee and S. Lee, "Validation and Development of the Driving Stress Scale," Korean J. of Culture and Social Issues, vol. 14, no. 3, 2008, pp. 21-40. 
  6. National Safety Council, "Understanding the Distracted Brain: Why Driving while Using Hand-free Cell Phone Is Risky Behavior," Report, Mar. 2010. 
  7. S. A. Hosseini, M. A. Khalilzadeh, and M. Branch, "Emotional Stress Recognition System Using EEG and Psychophysiological Signals: Using New Labelling Process of EEG Signals in Emotional Stress State," In Proc. Int. Conf. Biomedical Engineering and Computer Science, Wuhan, China, Apr. 2010. 
  8. R. Khosrowabadi, C. Quek, K. K. Ang, S. W. Tung, and M. Heijnen, "A Brain-Computer Interface for classifying EEG Correlates of Chronic Mental Stress," In Proc. Int. Joint Conf. Neural Networks (IJCNN), San Jose, CA, USA, Aug. 2011. 
  9. J. Choi and R. Gutierrez-Osuna, "Removal of Respiratory Influences from Heart Rate Variability in Stress Monitoring," IEEE Sensor J. vol. 11, no. 11, 2011, pp. 2649-2656.  https://doi.org/10.1109/JSEN.2011.2150746
  10. A. Santos, C. Sanchez, J. Guerra, and G. Bailador del Pozo, "A Stress-Detection System Based on Physiological Signals and Fuzzy Logic," IEEE Trans. Industrial Electronics, vol. 58, no. 10, 2011, pp. 4857-4865.  https://doi.org/10.1109/TIE.2010.2103538
  11. T. Yamakoshi, K. Yamakoshi, S. Tanaka, M. Nogawa, S. B. Park, M. Shibata, Y. Sawada, P. Rolfe, and Y. Hirose, "Feasibility Study on Driver's Stress Detection from Differential Skin Temperature Measurement," In Proc. 30th Annual Conf. IEEE in Engineering in Medicine and Biology Society, Vancouver, Canada, Aug. 2008. 
  12. Z. Jing, A. B. Barreto, C. Chin, and L. Chao, "Realization of stress Detection Using Psychophysiological Signals for Improvement of Human-Computer Interactions," In Proc. IEEE SoutheastCon, Fort Lauderdale, FL, USA, Apr. 2005. 
  13. J. A. Healey and R. W. Picard, "Detecting stress during real-world driving tasks using physiological sensors," IEEE Trans. Intelligent Transportation Systems, vol. 6, no. 2, 2005, pp. 156-166.  https://doi.org/10.1109/TITS.2005.848368
  14. B. Kim and B. Lee, "Bio-signal-based Driver's Emotional Response Monitoring System: System Implementation," J. of the Korea Institute of Electronics Communications Sciences, vol. 13, no. 3, 2018, pp. 667-683. 
  15. S. Hong, "Design and implementation of healthcare system based on non-contact biosignal measurement," J. of the Korea Institute of Electronics Communications Sciences, vol. 15, no. 1, 2020, pp. 185-190. 
  16. ISO 15031-3, Road vehicles - Communication between vehicle and external equipment for emissions-related diagnostics - Part 3: Diagnostic connector and related electrical circuits: Specification and use, ISO, 2016. 
  17. M. Kim, S. Lee, and S. Park, "A Development of EURO 6 Smart Cluster System Using OBD-II Standard Interfaces and Smart Cluster Interface," Trans. Korean Socity of Automotive Engineers, vol. 26, no. 1, 2018, pp. 85-96.  https://doi.org/10.7467/KSAE.2018.26.1.085
  18. SAE J1962, Diagnostic Connector Equivalent to ISO/DIS 15031, Society of Automotive Engineers, 2002. 
  19. H. D. Critchley, "Review: Electrodermal Responses: What Happens in the Brain," The Neuroscientist, vol. 8, no. 2 2002, pp. 132-142.  https://doi.org/10.1177/107385840200800209
  20. H. F. Posada-Quintero and K. H. Chon, "Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review," Sensors, vol. 20, no. 2, 2020, pp. 479. 
  21. E. Gulian, G. Matthews, A. I. Glendon, D. R. Davies, and L. M. Debney, "Dimensions of driver stress," Ergonomics, vol. 32, no. 6, 1989, pp. 585-602. https://doi.org/10.1080/00140138908966134