awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
udacity avatar

udacity/self-driving-car-simArchived

0
View on GitHub↗
3,985 stars·1,499 forks·C#·MIT·23 viewsudacity.com/self-driving-car↗

Self Driving Car Sim

This project is an autonomous vehicle simulator designed to validate self-driving logic and train deep learning algorithms within a virtual environment. It functions as a training platform for developing neural networks that control vehicle movement and steering based on visual sensor data.

The simulator uses the Unity game engine to provide a physics-based world where autonomous driving algorithms can be tested on virtual road courses without the use of physical hardware.

The system integrates a C# scripting backend with a physics engine for collision detection and vehicle dynamics. It utilizes raycast-based sensor simulation for obstacle detection and socket-based API communication to transmit simulation states and control commands to external deep learning models.

Features

  • Autonomous Vehicle Simulators - Provides a virtual environment for training and testing deep learning algorithms for autonomous vehicle navigation.
  • Deep Learning Training Toolsets - Functions as a training toolset for developing neural networks that control vehicle steering and movement.
  • Simulation Training Environments - Provides a simulation platform to develop neural networks that control vehicle movement based on visual sensor data.
  • Robotic Sensor Simulation - Simulates lidar and proximity sensors using raycasting to provide obstacle detection data for the vehicle.
  • Robotics Simulation Environments - Uses the Unity game engine to build a physics-based environment for testing autonomous vehicle behaviors.
  • 3D Physics Engines - Utilizes a 3D physics engine to calculate real-time vehicle dynamics and collision detection.
  • Procedural Instantiation - Uses procedural instantiation of prefabs to generate diverse road layouts and urban obstacles.
  • Virtual Course Testing - Evaluates how autonomous algorithms handle specific track layouts and obstacles in a repeatable digital setting.
  • Local-to-World Coordinate Transformations - Translates 3D world positions into localized vehicle coordinates for precise navigation and path planning.
  • Socket Communication - Employs socket communication to transmit simulation states and control commands to external deep learning models.
  • Robotics Simulation - Simulates self-driving cars in Unity.
  • Simulation Environments - Self-driving car simulator built with Unity.

Star history

Star history chart for udacity/self-driving-car-simStar history chart for udacity/self-driving-car-sim

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Projects sharing features with Self Driving Car Sim

These projects share indexed features with Self Driving Car Sim. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • facebookresearch/habitat-simfacebookresearch avatar

    facebookresearch/habitat-sim

    3,532View on GitHub↗

    Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents within photorealistic indoor and outdoor environments. It serves as a simulator for AI and robotics, providing a system for generating synthetic data and simulating physical interactions. The project is distinguished by a native C++ core that enables high-throughput simulation and a rendering pipeline using physically based rendering and baked global illumination. It features a navigation system based on pre-computed navigation meshes to ensure collision-free traversal and a rigi

    C++aicomputer-visioncplusplus
    View on GitHub↗3,532
  • eclipse/sumoeclipse avatar

    eclipse/sumo

    4,054View on GitHub↗

    SUMO is a microscopic traffic simulation suite designed to model the movement of individual vehicles and pedestrians across large-scale urban road networks. It functions as a multimodal transport simulator that integrates cars, pedestrians, bicycles, railways, and waterways within a single environment, supported by tools for road network generation and traffic demand modeling. The project distinguishes itself through specialized toolsets for environmental impact analysis, which calculate vehicle emissions and energy consumption for electric and hybrid fleets. It provides comprehensive capabil

    Python
    View on GitHub↗4,054
  • carla-simulator/carlacarla-simulator avatar

    carla-simulator/carla

    14,072View on GitHub↗

    CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving software. It functions as an urban traffic simulator that generates realistic vehicle and pedestrian behavior and as a synthetic sensor data generator producing LiDAR, Radar, and camera data. The platform distinguishes itself through its deep integration with robotics frameworks, specifically providing native connectivity to ROS2 nodes for robotic control and data processing. It supports the training of driving models via imitation and reinforcement learning within a controlle

    C++
    View on GitHub↗14,072
  • schteppe/cannon.jsschteppe avatar

    schteppe/cannon.js

    4,979View on GitHub↗

    cannon.js is a JavaScript 3D physics engine designed for calculating rigid body dynamics and collisions in three-dimensional space. It functions as a rigid body dynamics engine that models mass, friction, and velocity to determine object movement, while providing a mathematical framework for applying physical constraints and joints. The engine supports a variety of collision volumes, including spheres, boxes, convex polyhedrons, heightfields for terrain simulation, and complex triangle meshes. It provides tools for identifying intersections between these shapes and calculating the exact areas

    JavaScript
    View on GitHub↗4,979
Compare all 30 related projects→

Frequently asked questions

What does udacity/self-driving-car-sim do?

This project is an autonomous vehicle simulator designed to validate self-driving logic and train deep learning algorithms within a virtual environment. It functions as a training platform for developing neural networks that control vehicle movement and steering based on visual sensor data.

What are the main features of udacity/self-driving-car-sim?

The main features of udacity/self-driving-car-sim are: Autonomous Vehicle Simulators, Deep Learning Training Toolsets, Simulation Training Environments, Robotic Sensor Simulation, Robotics Simulation Environments, 3D Physics Engines, Procedural Instantiation, Virtual Course Testing.

Which projects share features with udacity/self-driving-car-sim?

Projects with overlapping indexed features include: facebookresearch/habitat-sim — Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents… eclipse/sumo — SUMO is a microscopic traffic simulation suite designed to model the movement of individual vehicles and pedestrians… carla-simulator/carla — CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving… schteppe/cannon.js — cannon.js is a JavaScript 3D physics engine designed for calculating rigid body dynamics and collisions in… dusty-nv/jetson-inference — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU… azazdeaz/fields-ignition — Generate random crop fields for Ignition Gazebo.