# ndrplz/self-driving-car

Udacity Self-Driving Car Engineer Nanodegree projects.

Repository: https://github.com/ndrplz/self-driving-car
Canonical: https://ross.abutalabs.com/products/ndrplz-self-driving-car
Language: C++
License Family: other
Topics: self-driving-car, udacity-self-driving-car, deep-learning, deep-neural-networks, kalman-filter, lecture-material, particle-filter, lane-finding, computer-vision, vehicle-detection, convolutional-neural-networks, detect-lane-lines, lane-detection, pid-control, traffic-sign-classification, tensorflow
Last push: 2023-03-28T00:13:06+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3538, "days_push": 1255, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2922, forks 1390 (observed 2026-08-28T04:07:30.258011+00:00)

## What it is
A collection of source code for all projects from the Udacity Self-Driving Car Engineer Nanodegree, covering lane finding, traffic sign classification, behavioral cloning, vehicle detection, Kalman/particle filters, path planning, and PID control. It serves as reference implementations and lecture material for learning autonomous vehicle algorithms.

## Use cases
- learn self-driving car algorithms from worked examples
- study lane detection with computer vision
- implement extended and unscented Kalman filters for sensor fusion
- train a CNN for traffic sign classification
- understand behavioral cloning for steering control
- reference particle filter localization code
- explore PID control for vehicle steering

## When to choose
- you are a student or engineer learning autonomous vehicle fundamentals
- you want reference implementations of classic self-driving course projects
- you need examples of Kalman filters, lane detection, or behavioral cloning

## When to avoid
- you need production-ready autonomous driving software
- you want a maintained library with a license and active development
- you need modern deep-learning-based perception pipelines

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: computer-vision, machine-learning, deep-learning, simulation
- domain: autonomous-vehicles, computer-vision, machine-learning, tutorials, robotics
- platform: cpp, python, cross-platform
- tags: self-driving-car, udacity-nanodegree, kalman-filter, particle-filter, lane-detection, vehicle-detection, behavioral-cloning, pid-control, traffic-sign-classification, course-projects

## Member repositories
- ndrplz/self-driving-car (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:30.258011+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:33:46.274717+00:00, confidence not recorded.
  - readme: https://github.com/ndrplz/self-driving-car (fetched 2026-08-28T04:07:30.258011+00:00, sha 25a9be641aea)
- Data as of 2026-08-30T08:39:29.467469+00:00.