AVTONOM TRANSPORT VOSITALARIDA REAL VAQTDA QAROR QABUL QILISH ALGORITMLARINI TAKOMILLASHTIRISH
DOI:
https://doi.org/10.65164/93gvyb77Kalit so‘zlar:
avtonom transport, real vaqtda qaror qabul qilish, chuqur kuchaytiruvchi o‘rganish, Model Predictive Control, sensor fuziyasi, xavfsizlik algoritmi, CARLA simulyator, o‘z-o‘zini boshqaruvchi avtomobil, aqlli transport, robototexnikaAbstrak
Ushbu tadqiqot avtonom transport vositalarida (ATV) real vaqtda qaror qabul qilish algoritmlarini takomillashtirish muammosini kompleks o‘rganishga bag‘ishlangan. ATV tizimlari zamonaviy sun’iy intellekt va robototexnika sohasining eng murakkab amaliy masalalaridan birini ifodalaydi: millisekundlar ichida ko‘p parametrli, cheksiz holat fazosida xavfsiz va optimal qarorlar qabul qilish. Tadqiqotda Deep Reinforcement Learning (DRL), Model Predictive Control (MPC) va Hybrid AI yondashuvlarining real vaqtda ishlash samaradorligi qiyosiy tahlil qilingan. CARLA, SUMO va MATLAB/Simulink simulyatsiya muhitlarida o‘tkazilgan eksperimentlar asosida yig‘ish vaqti (latency), xavfsizlik ko‘rsatkichlari va hisoblash samaradorligi bo‘yicha batafsil natijalar keltirilgan. Taklif etilgan gibrid DRL-MPC algoritmi an’anaviy MPC algoritmiga nisbatan qaror qabul qilish vaqtini 38% ga qisqartirgan va xavfsizlik holatlarini aniqlash aniqligini 94.7% ga yetkazgan. Tesla, Waymo va NVIDIA kabi yetakchi kompaniyalar ma’lumotlari va SAE International standartlari asosida tahlil o‘tkazilgan bo‘lib, natijalar O‘zbekistonning aqlli transport tizimlarini rivojlantirish kontekstida muhokama qilingan
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asosida yo‘l chiziqlarini vizuallashtirish ISSN: 2181-2020. «Eurasian Journal of Academic
Research» ilmiy-uslubiy jurnali: №12 Maxsus son. 2024 yil. 105-109 betlar.
2. A.A.Bahromov, F.A.Jo‘raboyev Virtual reallik texnologiyalarining matematik modellarini
tahlil qilish ISSN: 2181-2020. «Eurasian Journal of Academic Research» ilmiy-uslubiy
jurnali: №12 Maxsus son. 2024 yil. 811-813 betlar.
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