Decoupled Perception-Actuation Architecture for Low-Cost Level 2 ADAS Prototyping Using YOLO and ESP32
Year: 2026
Type: article
Abstract: Advanced Driver Assistance Systems (ADAS) are transforming modern transportation, but their proprietary and expensive nature limits accessibility for students and independent researchers. This paper presents the development of a low-cost, functional Level 2 autonomous vehicle prototype that bridges the gap between advanced perception software and reproducible hardware. Our architecture decouples high-level computer vision from low-level physical actuation. An external computational unit processes wireless visual telemetry using OpenCV for nearest-pair lane tracking and a fine-tuned YOLO model for dynamic object and traffic sign recognition. Navigation commands are transmitted via UDP to an ESP32 microcontroller, which executes precise motor control using a Proportional-Integral-Derivative (PID) algorithm. The ESP32 has built-in hardware reflexes like ultrasonic emergency braking and an infrared-triggered corrective steering reflex for lane correction to make sure safety no matter how slow the network is. Experimental results demonstrate a 90 percent object detection success rate under optimal lighting and highly reliable obstacle avoidance, while also highlighting the environmental limitations of single-camera visual telemetry. This project proves that complex autonomous driving logic can be effectively simulated and studied on an affordable, small-scale platform.
Author: Ahir, Jaydeep
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7155209205
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