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This article presents a modified method for determining the activation timing of airbags in vehicles, which incorporates the real-time position of the driver’s and passengers’ heads. The primary objective of this modification is to improve the precision of airbag deployment by introducing an additional parameter—namely, the actual head position of the vehicle occupants, monitored in real time. The use of cameras and advanced image processing algorithms enables continuous tracking of head positions. As a result, the airbag system can adjust its activation timing according to the current positions of the occupants during a collision, significantly enhancing protective effectiveness. The results show that reducing the distance of the head from the normalized position by 70 mm requires the airbag activation to be advanced by an average of 28%. The largest correction occurs at a speed of 23 km/h and reaches 30%, decreasing at higher speeds. Conversely, increasing the distance by 70 mm necessitates the activation to be delayed by an average of 22%, with a maximum correction of 23% also observed at 23 km/h. These differences arise from the variable deceleration profile during a crash, which is influenced by specific collision dynamics. Unlike the conventional “13-30” model, which assumes a fixed head-to-airbag distance, the new method accounts for actual variations in occupant positioning, thereby improving protective performance. The proposed system uses infrared cameras and a lidar unit to track reference points on the head, such as the center of the forehead and the chin. Based on the collected data, the system dynamically adjusts the airbag deployment timing, reducing the risk of head injuries. This method can be integrated with other safety systems, such as seatbelt pretensioners and adaptive headrests, and is particularly applicable in autonomous vehicles, for which occupant positions may deviate significantly from standard seating postures. Adaptive airbag deployment has the potential to become a new standard in enhancing road safety.
Czasopismo
Rocznik
Tom
Strony
149--160
Opis fizyczny
Bibliogr. 21 poz.
Twórcy
autor
- West Pomeranian University of Technology in Szczecin, Department of Automotive Engineering; Piastow av. 19, 70-310 Szczecin, Poland
autor
- West Pomeranian University of Technology in Szczecin, Department of Automotive Engineering; Piastow av. 19, 70-310 Szczecin, Poland
autor
- West Pomeranian University of Technology in Szczecin, Department of Automotive Engineering; Piastow av. 19, 70-310 Szczecin, Poland
autor
- West Pomeranian University of Technology in Szczecin, Department of Automotive Engineering; Piastow av. 19, 70-310 Szczecin, Poland
autor
- West Pomeranian University of Technology in Szczecin, Department of Thermal Technologies and Safety Engineering; Piastów av. 41, 71-065 Szczecin, Poland
Bibliografia
- 1. Byoung-Keon Park, D.J. & Kozak, K. & Reed, M.P. Model-based characterisation of vehicle occupants using a depth camera. International Journal of Vehicle Design. 2020. P. 23-37. DOI: 10.1504/IJVD.2020.114780.
- 2 Ching-Yao, Ch. Fundamentals of Crash Sensing in Automotive Air Bag Systems. Published by SAE International. 2000. ISBN: 9780768063783.
- 3. Hadrys, D. & Kubik, A. & Stanik, Z. Deceleration and deformation during dynamic loading of model car body parts after post-accident repair. Transport Problems. 2020. Vol. 15. No. 3. P. 5-16.
- 4. Hannan, M.A. & Hussai, A. & Mohamed, A. et al. Decision fusion of a multi-sensing embedded system for occupant safety measures. International Journal of Automotive Technology. 2010. Vol. 11.No. 1.P. 57-65.
- 5. Gałdynski, D. & Abramek, K.F. & Lisowski, M. et al. Heuristic model for assessing disruptions in the synchronization of airbag deployment with the driver’s body during a collision, based on repaired longitudinal beams. Transport Problems. 2024. Vol. 19 No. 1. P. 131-142.
- 6. International Motor Vehicle Inspection Committee Raport 8328. A Test Procedure for Airbags. Institut für Kraftfahrwesen Aachen. 2000.
- 7. Jain, A.K. & Farmer, M.E. Smart automotive airbags: Occupant classification and tracking. IEEE Transactions on Vehicular Technology. 2007. P. 60-80.
- 8. Kamiński, T. & Niezgoda, M. & Kruszewski, M. Collision detection algorithms in the ecall system. Journal of KONES Powertrain and Transport. 2012. Vol. 19. No. 4. P. 267-274.
- 9. Kirmas, A. & Lemcke, S. & Böshagen, S. et al. Head tracking in automotive environments for driver monitoring using a low resolution thermal camera. Vehicles. 2022. No. 4. P. 219-233.
- 10. Mishra, A. & Lee, S. & Kim, D. & Kim, S. In-cabin monitoring system for autonomous vehicles. Sensors 2022. Vol. 22. No. 4360.
- 11. NHTSA VSR - NHTSA Vehicle Crash Test Database. No. crashtest: TC 03-228 RR04-232, Tc 03229 RR04-221, DTS-TRC-03-005, 030806-1, 060502-1, NCAP-MGA-2001-004). Available at: https://www-nrd.nhtsa.dot.gov/database/veh/veh.htm.
- 12. Patent JP2010100142. Vehicular Device Control Device. Toyota Motor Corp, Japan. (Uozumi, S.) Publ. 06.05.2010.
- 13. Patent DE10308405. Airbag Control Methodfor Motor Vehicle, Uses Camera to Determine Actual Position of Vehicle Occupant’s Head with Respect to Preset Position to Control Airbag Ignition. Bayerische Motoren Werke AG, Germany. (Augst, A. & Borke, D. & Durach, S.) Publ. 27.02.2003.
- 14. Patent JP2006290258. Occupant Restraining Device. Honda Motor Co Ltd, Japan. (Takemura, N.) Publ. 13.04.2005.
- 15. Patent CN110395208. Control the air bag activation state at motor vehicles. Ford Global Technologies LLC. Chinese. Publ. 01.11.2019.
- 16. Patent US10131309. Apparatus and method for controlling airbag. Hyundai Motor Co. US. (Seon, A. K.) Publ. 20.11.2018.
- 17. Rastegar, V. & Marzbanrad, J. Modeling and simulation of vehicle airbag behaviour in crash. International Scientific Journal “Industry 4.0”. 2018. Vol. 3. P. 126-129.
- 18. Trivedi, M.M. & Krotosky, S.J. & Cheng, S.Y. Face detection and head tracking using stereo and thermal infrared cameras for “smart” airbags: a comparative analysis. Proceedings The 7th International IEEE Conference on Intelligent Transportation Systems. 2004. P. 17-22.
- 19. Wang, X. & Luo, Z. & Liu, Y. & Ling F. Fatigue properties of advanced high strength steel plate welded by hybrid plasma arc welding. Procedia Structural Integrity. 2019. Vol. 22. P. 59-63.
- 20. Winch, M. & Hollowell, T.W. & Kanianthra, J. & Evans, W.D. Air Bag Technology in light passenger vehicles. Office of Research and Development National Highway Traffic Safety Administration. USA. 2001.
- 21. Vangi, D. Vehicle Collision Dynamics, Analysis and Reconstruction. Department of Industrial Engineering, University of Florence. Italy. 2020.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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