Matrix LED Adaptive Headlight System

A simplified replica of modern adaptive headlight systems found in vehicles, using a matrix of LEDs, real-time sensor input, and Rust-powered control logic running on a Raspberry Pi Pico 2W.

info

Author: Eduard-Andrei Balaceanu
GitHub Project Link:: https://github.com/UPB-PMRust-Students/project-eduard1506

Description

This project showcases the knowledge acquired throughout the semester by designing a functional hardware system that runs software written entirely in Rust. The system replicates a simplified version of the adaptive headlight functionality found in modern vehicles, using a matrix of LEDs controlled by a Raspberry Pi Pico 2W microcontroller.

The setup includes multiple white LEDs arranged in a grid, which dynamically turn on/off or dim based on real-time sensor input. The system uses light sensors to detect the presence and direction of oncoming lights, and a distance sensor to identify nearby objects. It also features adaptive cornering simulation using a joystick input.

The goal is to demonstrate real-time hardware control, sensor input interpretation, and modular embedded design using the Rust programming language.

Motivation

One of my biggest passions is cars—and everything they represent. I've always loved the feeling of a late-night drive, but to truly enjoy it, you need a powerful and intelligent lighting system. Matrix LED headlights represent the pinnacle of automotive lighting technology, adapting dynamically to changing road conditions, light sources, and traffic.

I’ve been fascinated by how this system works, how it improves both safety and comfort, and why it isn’t more widely adopted across all types of vehicles. Through this project, I wanted to explore the core principles behind adaptive lighting and bring a simplified version to life using accessible components and Rust-based control logic.

Architecture

The system architecture consists of the following functional layers:

1. Sensor Layer

   • Three ambient light sensors (TEMT6000) detect the direction and intensity of incoming light sources.
   • One ultrasonic sensor (HC-SR04) measures the distance to nearby objects.

2. Input Layer

   • A joystick is used to simulate vehicle steering input for adaptive cornering.

3. Control Layer

   • A Raspberry Pi Pico 2W reads input data from all sensors.
   • A custom control algorithm written in Rust determines which LEDs should be turned on, off, or dimmed.

4. Output Layer

   • A matrix of white LEDs is powered and controlled via IRLZ44N MOSFETs.
   • The system dims or disables individual LEDs based on sensor input to avoid blinding oncoming traffic while preserving road visibility.

5. Feedback Layer (Planned)

   • A small OLED display will be used to show real-time system feedback such as active LEDs, steering direction, and sensor status.

Each component is connected using breadboards and jumper wires, with careful power and grounding design to ensure stability. The entire system operates without external Wi-Fi or cloud dependency, functioning in a fully local, embedded environment.

Diagram

Weekly Log

Week 8 – May 4th

Over the past few weeks, I’ve been gathering all the necessary components for the project. After pitching my idea to the professor and getting the green light, I decided to attempt building a simplified version of the Matrix LED adaptive headlight system used in modern vehicles.

This week marked the official start of the documentation process. I’ve already experimented with wiring the Pico 2W, tested the debugger, and ran a few simple LED blink tests in Rust to confirm everything’s working. Most of the hardware is now in place — the MOSFETs, LEDs, sensors, and breadboards — though I’m still waiting on the OLED screen and joystick module.

I also started working on the architecture diagram using diagrams.net. I’m aiming to create something clean and professional, so the structure makes sense both visually and logically. Once that’s done, I’ll export it and integrate it into the site. Documentation is coming together nicely so far.

Hardware Design

The hardware implementation is still in progress, but the core setup has already been planned and partially assembled. The project is built around a Raspberry Pi Pico 2W microcontroller, connected to a matrix of white LEDs via IRLZ44N MOSFETs.

Sensor inputs include three ambient light sensors, an ultrasonic distance sensor, and a joystick to simulate adaptive cornering input. Power is delivered through a regulated breadboard power supply, and connections are made using standard jumper wires across two breadboards.

A schematic will be added once final wiring is complete.

Bill of Materials

Device	Usage	Price
Raspberry Pi Pico W	The microcontroller	35 RON
Breadboard	The main breadboard	10 RON
Light Sensors (x3)	Measure ambient light	3 x 9.99 RON
Ultrasonic Sensor	Detect object distance	6.49 RON
Joystick Module	Manual control for LED direction	11.99 RON
MOSFETs (IRLZ44N x6)	Drive high-power LEDs	6 x 4.99 RON
LED Assortment	Visual output (matrix lighting)	26.99 RON
OLED Display (0.96")	Diagnostic feedback	23.79 RON

Software

Library	Description	Usage
heapless	Data structure library	Used for String vectors
embassy_rp	Embassy HAL for the Raspberry Pi RP2040	Used to program the Pico
embassy_sync	Sync primitives and async data support	Communicating through tasks
embedded-hal	Hardware abstraction traits	Common interface for embedded peripherals
ssd1306	OLED display driver	Drives the OLED via I2C
defmt, defmt-rtt	Lightweight logging + RTT interface	Debugging via the probe
cortex-m	ARM Cortex-M microcontroller support	Low-level control
cortex-m-rt	Runtime support	Startup and interrupts
panic-halt	Panic behavior	Safe stop on crash