DOI QR코드

DOI QR Code

Vehicles Auto Collision Detection & Avoidance Protocol

  • Received : 2022.03.05
  • Published : 2022.03.30

Abstract

The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

Keywords

References

  1. E. Coelingh, L. Jakobsson, H. Lind, and M. Lindman, "Collision warning with auto brake: a real-life safety perspective," Innovations for Safety: Opportunities and Challenges, 2007.
  2. Y. Gao, F. J. Jiang, L. Xie, and K. H. Johansson, "Risk-Aware Optimal Control for Automated Overtaking With Safety Guarantees," IEEE Transactions on Control Systems Technology, 2021.
  3. R. W. Anderson, D. J. Searson, and T. P. Hutchinson, "Integrating the assessment of pedestrian safety in vehicles with collision detection and mitigation systems," in Proceedings of IRCOBI conference, 2012, pp. 751-760.
  4. H. Hamdane, "Improvement of Pedestrian Safety: Response of detection systems to real accident scenarios," 2016.
  5. V. Goud, "Vehicle accident automatic detection and remote alarm device," International Journal of Reconfigurable and Embedded Systems, vol. 1, p. 49, 2012. https://doi.org/10.11591/ijres.v1.i2.pp49-54
  6. S. P. Shubham, M. Kumar, and S. Jain, "A Survey on IoT based Automatic Road Accident Detection," in 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), 2021, pp. 1-7.
  7. I. C. Ijeh, "A collision-avoidance system for an electric vehicle: a drive-by-wire technology initiative," SN Applied Sciences, vol. 2, pp. 1-20, 2020. https://doi.org/10.1007/s42452-019-1685-8
  8. A. M. Zungeru, "Development of an Anti-collision Model for Vehicles," arXiv preprint arXiv:1212.5440, 2012.
  9. S. Ren, Y. He, N. N. Xiong, and K. Guo, "Towards Class-incremental Object Detection with Nearest Mean of Exemplars," arXiv preprint arXiv:2008.08336, 2020.
  10. F. D. Salim, S. W. Loke, A. Rakotonirainy, and S. Krishnaswamy, "U&I aware: A framework using data mining and collision detection to increase awareness for intersection users," in 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007, pp. 530-535.
  11. P. Arun, G. Sabarinath, S. Madhukumar, and P. Careena, "Implementaion of zigbee based train anti-collision and level crossing protection system for indian railways," International Journal of latest trends in Engineering and Technology, vol. 2, pp. 12-18, 2013.
  12. S. Banerjee, S. Mondal, A. Chakraborty, and S. Chattaraj, "Global Positioning System Based Automated Railway Level Crossing," in 2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE), 2020, pp. 1-4.
  13. J. Lee, Y. Hwang, and K. Yang, "Intelligent Collision Prevention Technique for Construction Equipment using Ultrasound Scanning," Korean Journal of Construction Engineering and Management, vol. 22, pp. 48-54, 2021. https://doi.org/10.6106/KJCEM.2021.22.5.048
  14. A. Oloufa, M. Ikeda, and H. Oda, "GPS-based wireless collision detection of construction equipment," NIST Special Publication sp, pp. 461-466, 2003.
  15. A. Anil, V. K. Shukla, and V. Naranje, "Tracking Vehicles through GPS Module and Arduino UNO," in 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), 2021, pp. 1-6.
  16. A. Ben-Yaacov, M. Maltz, and D. Shinar, "Effects of an in-vehicle collision avoidance warning system on short-and long-term driving performance," Human Factors, vol. 44, pp. 335-342, 2002. https://doi.org/10.1518/0018720024497925
  17. M. Zhu, X. Wang, and J. Hu, "Impact on car following behavior of a forward collision warning system with headway monitoring," Transportation research part C: emerging technologies, vol. 111, pp. 226-244, 2020. https://doi.org/10.1016/j.trc.2019.12.015
  18. J. White, C. Thompson, H. Turner, B. Dougherty, and D. C. Schmidt, "Wreckwatch: Automatic traffic accident detection and notification with smartphones," Mobile Networks and Applications, vol. 16, pp. 285-303, 2011. https://doi.org/10.1007/s11036-011-0304-8
  19. L. Parziale, W. Liu, C. Matthews, N. Rosselot, C. Davis, J. Forrester, et al., "TCP/IP tutorial and technical overview," 2006.
  20. G. GOV, "Control segment," ed.