Self-Driving Car Using Raspberry Pi
π Overview
Build a self-driving prototype with a Raspberry Pi and a camera: the camera sees the road and the lane lines, image processing computes a steering angle, and a PID controller drives the servo and motor to follow the lane.
The project ties computer vision to a control system end to end - a classic case study in introductory self-driving education.
π§° What you need
- Raspberry Pi (3B/4B) + camera module
- Robot chassis + motors + motor driver board (L298N and similar)
- Steering servo + battery pack
- Python 3 + OpenCV + numpy
- Optional: VNC/SSH over the local network for debugging
π§ Step by step
Build the car platform
Assemble the chassis, motors, and steering servo
Verify with simple code that the motors and servo respond correctly
Set up the Raspberry Pi
Flash the OS and configure the camera and SSH
Install OpenCV and its dependencies (a prebuilt wheel speeds this up)
Capture the road view
Point the camera at the road ahead and check the image quality
Make sure the full lane line is visible in frame
Detect the lane lines
Extract the lane region with colour filtering or edge detection
Fit the lane line with a Hough transform or a sliding window
Compute the steering angle
Derive the target steering angle from the lane-centre offset
Use the difference between the frame centre and the lane centre as the error signal
PID control
Run the error through a PID loop to produce the servo angle
Tune P first, then add I and D to remove steady-state error
Tune the closed loop
Start on a slow straight, then move on to curves
Adjust speed and steering gain so the car does not fly off the track
π‘ Tips
- The lane detection thresholds are very sensitive, so calibrate on still images before driving the real car
- Tune each PID term separately and change only one thing at a time
- Safety first: test in an enclosed area and keep an emergency stop and a manual override