Author: Urinova, Gulxayo Sarvarovna; Lee, Seungjik

Annotation: This article analyzes an approach to adaptive control of autonomous and semi-autonomous vehicles in Uzbekistan based on IoT sensors and computer vision technologies. The study examines, from a computer engineering perspective, the dynamics of road traffic accidents in Uzbekistan during 2021–2026, the growth of the vehicle fleet, automated photo and video enforcement systems, the national “Safe and Smooth Road” program, and regulatory measures aimed at digitalizing road safety management. International practices from the European Union, the United States, Singapore, China, the United Kingdom, South Korea, and C-ITS/V2X systems are reviewed. The article proposes an IoT–Computer Vision–Fusion-based ICF-ABM model. Within this model, data on pavement condition, weather, traffic flow, pedestrians, traffic lights, road signs, and hazardous objects are integrated into a unified road risk index. The proposed model enables real-time risk assessment and supports adaptive decisions related to speed control, safe following distance, braking strategy, and trajectory selection. The model is intended to shift road safety management from reactive violation recording to proactive risk prediction and adaptive vehicle control.

Keywords: IoT sensors, computer vision, autonomous vehicle, adaptive control, sensor fusion, risk index, road conditions, V2X, C-ITS, edge computing.

Pages in journal: 293 - 306