Ushbu maqolada sun‘iy intellekt texnologiyalari asosida haydovchilar charchoqligini real vaqtda aniqlash va yo‘l-transport hodisalarini oldini olish tizimlari tahlil qilinadi. Haydovchi charchoqligi yo‘l xavfsizligiga tahdid soluvchi asosiy omillardan biri hisoblanadi va har yili minglab odamlarning hayotiga xavf tug‘diradi. Maqolada kompyuter ko‘rishi, chuqur o‘rganish algoritmlari, sensor texnologiyalari va fiziologik parametrlarni kuzatish tizimlari orqali charchoqlikni aniqlash metodlari ko‘rib chiqiladi.
Sun‘iy intellekt, haydovchi charchoqligi, yo‘l xavfsizligi, kompyuter ko‘rishi
1. World Health Organization (WHO), "Global Status Report on Road Safety
2023." Geneva: WHO Press, 2023.
2. Sahayadhas, A., Sundaraj, K., & Murugappan, M. "Detecting driver drowsiness
based on sensors: A review." Sensors, 2012, 12(12), pp. 16937-16953.
3. Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. "You only look once:
Unified, real-time object detection." Proceedings of the IEEE Conference on Computer
Vision and Pattern Recognition, 2016, pp. 779-788.
4. Hochreiter, S., & Schmidhuber, J. "Long short-term memory." Neural
Computation, 1997, 9(8), pp. 1735-1780.
5. Daimler AG, "Mercedes-Benz ATTENTION ASSIST: Technical
Documentation." Stuttgart: Daimler Technical Information, 2020.