This study presents a scalable, low-cost implementation of core autonomous functions using an embedded modular testbed, designed for real-time responsiveness and educational utility. The system integrates key behaviors - lane keeping, emergency braking, overtaking, and parallel parking - through efficient rule-based logic optimized for microcontroller hardware. These modules are validated through structured closed-environment tests, demonstrating safe and repeatable operation. Beyond hardware, the platform advances cognitive mobility by showing how embedded systems can perceive their environment, apply decision logic, and execute adaptive actions under real-world constraints. It serves as a compact cognitive testbed for evaluating autonomous behavior within limited computational resources. The architecture prioritizes simplicity and expandability, offering a robust foundation for future upgrades such as sensor fusion, adaptive control, or energy-aware algorithms. The main takeaway of this work is the demonstration that essential autonomous driving behaviors can be reliably prototyped and validated using a modular, microcontroller-based platform - supporting iterative development, cost-effective experimentation, and scalable integration of more advanced control layers.