Every year there are many people die or become injured due to car crashes around the world- -these injuries can vary from slight to severe. Airbags prevent car accident related injury and death. In order for the airbag to operate successfully (i.e., airbag to deploy properly, at the right speed, for the right amount of time) there has to be a decrease in the time that it takes to deploy the airbag and an increase in the minimum force necessary to deploy the airbag. This research is used to determine the different ways of airbag usage with and without mounting airbag at the time of collision. In this paper, it also describes a collision detection system with algorithm using FPGAs and sensor fusions in the high speed aircraft. This paper uses sensor fusion, which is a combination of pre-collision sensors such as accelerometer sensors and gyroscope sensors and post-campaign sensors such as pressure sensors and vibration sensors. These sensors can be fused together to be used to detect crashes accurately and to cause less false alarms if enough time has passed. Determining crash severity level and required action for the passenger are two main reasons that airbag deployment must occur in real-time embedded systems, therefore, this paper discusses sensor fusion and decision making process for these reasons. Meanwhile the real-time sensor data acquirement and decision making process are implemented on a Field Programmable Gate Array (FPGA). By introducing the sensor fusion inside the FPGA for airbag deployment systems, the parallelism and the datasheets of airbag relate to the real time system like the timing constraints are higher, hence the reliability and the safety of the system is improved. The course of this article includes current advancements in airbag deployment for all passengers from previous years and the continued direction in which these advancements may continue.

Keywords - FPGAs, Crash Detection, Sensor Fusion or Collision Severity Estimation, Ejection Airbags, Vibration Sensors, Pressure Sensors

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1. Roy S, Kumari A, Roy P, Banerjee R. An arduino based automatic accident detection and location communication system. In2020 IEEE 1st International Conference for Convergence in Engineering (ICCE) 2020 Sep 5 (pp. 38-43). IEEE.
2. Agrawal AK, Agarwal K, Choudhary J, Bhattacharya A, Tangudu S, Makhija N. Automatic traffic accident detection system using ResNet and SVM. In2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) 2020 Nov 26 (pp. 71-76). IEEE.
3. Kapilan K, Bandara S, Dammalage T. Vehicle accident detection and warning system for sri lanka using gnss technology. In2020 International Conference on Image Processing and Robotics (ICIP) 2020 Mar 6 (pp. 1-5). IEEE.
4. Karmokar P, Bairagi S, Mondal A, Nur FN, Moon NN, Karim A, Yeo KC. A novel IoT based accident detection and rescue system. In2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT) 2020 Aug 20 (pp. 322-327). IEEE.
5. Cho K, Choi SB, Lee H. Design of an airbag deployment algorithm based on precrash information. IEEE Transactions on Vehicular Technology. 2011 Mar 14;60(4):1438-52.
6. Manuja M, Kowshika S, Narmatha S, Theresa G. IoT based automatic accident detection and rescue management in Vanet. SSRG Int. J. Comput. Sci. Eng.. 2019 Feb;2:36-41..
7. Aljazzar H, Fischer M, Grunske L, Kuntz M, Leitner-Fischer F, Leue S. Safety analysis of an airbag system using probabilistic FMEA and probabilistic counterexamples. In2009 Sixth International Conference on the Quantitative Evaluation of Systems 2009 Sep 13 (pp. 299- 308). IEEE.
8. Altendorfer R, Wirkert S, Heinrichs-Bartscher S. Sensor fusion as an enabling technology for safety-critical driver assistance systems. SAE International Journal of Passenger Cars-Electronic and Electrical Systems. 2010 Oct 19;3(2010-01-2339):183-92.
9. Hussain A, Hannan MA, Mohamed A, Sanusi H, Majlis BY. Decision algorithm for smart airbag deployment safety issues. International Journal of Electrical and Computer Engineering. 2006;1(1):31-7.
10. Ren R, Li H, Han T, Tian C, Zhang C, Zhang J, Proctor RW, Chen Y, Feng Y. Vehicle crash simulations for safety: Introduction of connected and automated vehicles on the roadways. Accident Analysis & Prevention. 2023 Jun 1;186:107021.
11. Baballe MA. Accident detection system with gps, gsm, and buzzer. TMP Universal Journal of Research and Review Archives. 2023 Mar 15;2(1):28-36.
12. Grigorev A, Mihăiţă AS, Saleh K, Chen F. Automatic accident detection, segmentation and duration prediction using machine learning. IEEE Transactions on Intelligent Transportation Systems. 2023 Oct 18;25(2):1547-68.
13. Hossain I, Islam MS, Sultana R, Latif MA. Automatic Vehicle Accident Detection and Messaging System Using GSM and GPS Module. Int J Res Appl Sci Eng Technol. 2023 Sep;11(9):1166-75.
14. Ali HM, Alwan ZS. Car accident detection and notification system using smartphone. Saarbrucken: Lap Lambert Academic Publishing; 2017.
15. Ramdasi D, Bhoge L, Jiby B, Pembarti H, Phadatare S. Iot-based automotive collision avoidance and safety system for vehicles. InCongress on Intelligent Systems 2022 Sep 5 (pp. 667-681). Singapore: Springer Nature Singapore.
16. Elaidy A, Rayner R, Kalyvas C. Innovative design of external airbag system for improved automotive safety. IEEE Open Journal of Vehicular Technology. 2024 Jul 16;5:967-78.

Every year there are many people die or become injured due to car crashes around the world- -these injuries can vary from slight to severe. Airbags prevent car accident related injury and death. In order for the airbag to operate successfully (i.e., airbag to deploy properly, at the right speed, for the right amount of time) there has to be a decrease in the time that it takes to deploy the airbag and an increase in the minimum force necessary to deploy the airbag. This research is used to determine the different ways of airbag usage with and without mounting airbag at the time of collision. In this paper, it also describes a collision detection system with algorithm using FPGAs and sensor fusions in the high speed aircraft. This paper uses sensor fusion, which is a combination of pre-collision sensors such as accelerometer sensors and gyroscope sensors and post-campaign sensors such as pressure sensors and vibration sensors. These sensors can be fused together to be used to detect crashes accurately and to cause less false alarms if enough time has passed. Determining crash severity level and required action for the passenger are two main reasons that airbag deployment must occur in real-time embedded systems, therefore, this paper discusses sensor fusion and decision making process for these reasons. Meanwhile the real-time sensor data acquirement and decision making process are implemented on a Field Programmable Gate Array (FPGA). By introducing the sensor fusion inside the FPGA for airbag deployment systems, the parallelism and the datasheets of airbag relate to the real time system like the timing constraints are higher, hence the reliability and the safety of the system is improved. The course of this article includes current advancements in airbag deployment for all passengers from previous years and the continued direction in which these advancements may continue.

Keywords - FPGAs, Crash Detection, Sensor Fusion or Collision Severity Estimation, Ejection Airbags, Vibration Sensors, Pressure Sensors

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Roy S, Kumari A, Roy P, Banerjee R. An arduino based automatic accident detection and location communication system. In2020 IEEE 1st International Conference for Convergence in Engineering (ICCE) 2020 Sep 5 (pp. 38-43). IEEE.
2. Agrawal AK, Agarwal K, Choudhary J, Bhattacharya A, Tangudu S, Makhija N. Automatic traffic accident detection system using ResNet and SVM. In2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) 2020 Nov 26 (pp. 71-76). IEEE.
3. Kapilan K, Bandara S, Dammalage T. Vehicle accident detection and warning system for sri lanka using gnss technology. In2020 International Conference on Image Processing and Robotics (ICIP) 2020 Mar 6 (pp. 1-5). IEEE.
4. Karmokar P, Bairagi S, Mondal A, Nur FN, Moon NN, Karim A, Yeo KC. A novel IoT based accident detection and rescue system. In2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT) 2020 Aug 20 (pp. 322-327). IEEE.
5. Cho K, Choi SB, Lee H. Design of an airbag deployment algorithm based on precrash information. IEEE Transactions on Vehicular Technology. 2011 Mar 14;60(4):1438-52.
6. Manuja M, Kowshika S, Narmatha S, Theresa G. IoT based automatic accident detection and rescue management in Vanet. SSRG Int. J. Comput. Sci. Eng.. 2019 Feb;2:36-41..
7. Aljazzar H, Fischer M, Grunske L, Kuntz M, Leitner-Fischer F, Leue S. Safety analysis of an airbag system using probabilistic FMEA and probabilistic counterexamples. In2009 Sixth International Conference on the Quantitative Evaluation of Systems 2009 Sep 13 (pp. 299- 308). IEEE.
8. Altendorfer R, Wirkert S, Heinrichs-Bartscher S. Sensor fusion as an enabling technology for safety-critical driver assistance systems. SAE International Journal of Passenger Cars-Electronic and Electrical Systems. 2010 Oct 19;3(2010-01-2339):183-92.
9. Hussain A, Hannan MA, Mohamed A, Sanusi H, Majlis BY. Decision algorithm for smart airbag deployment safety issues. International Journal of Electrical and Computer Engineering. 2006;1(1):31-7.
10. Ren R, Li H, Han T, Tian C, Zhang C, Zhang J, Proctor RW, Chen Y, Feng Y. Vehicle crash simulations for safety: Introduction of connected and automated vehicles on the roadways. Accident Analysis & Prevention. 2023 Jun 1;186:107021.
11. Baballe MA. Accident detection system with gps, gsm, and buzzer. TMP Universal Journal of Research and Review Archives. 2023 Mar 15;2(1):28-36.
12. Grigorev A, Mihăiţă AS, Saleh K, Chen F. Automatic accident detection, segmentation and duration prediction using machine learning. IEEE Transactions on Intelligent Transportation Systems. 2023 Oct 18;25(2):1547-68.
13. Hossain I, Islam MS, Sultana R, Latif MA. Automatic Vehicle Accident Detection and Messaging System Using GSM and GPS Module. Int J Res Appl Sci Eng Technol. 2023 Sep;11(9):1166-75.
14. Ali HM, Alwan ZS. Car accident detection and notification system using smartphone. Saarbrucken: Lap Lambert Academic Publishing; 2017.
15. Ramdasi D, Bhoge L, Jiby B, Pembarti H, Phadatare S. Iot-based automotive collision avoidance and safety system for vehicles. InCongress on Intelligent Systems 2022 Sep 5 (pp. 667-681). Singapore: Springer Nature Singapore.
16. Elaidy A, Rayner R, Kalyvas C. Innovative design of external airbag system for improved automotive safety. IEEE Open Journal of Vehicular Technology. 2024 Jul 16;5:967-78.