Segmenting various features of the road to make it easier for self-driving cars to take decisions by using image processing techniques and a U-Net Neural Network

An Integrated Cyber-Physical Ecosystem for Autonomous Driving Research and Education

A tool for predicting unsafe road scenarios for self-driving cars in BeamNG.tech.

Notes and key takeaways of the Self-Driving Cars Perception applied Deep Learning Free Course from freeCodeCamp.org

Self-Driving Cars with ROS and Autoware opensource stack by Autoware Foundation hosted by ApexAI.

Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]

Reinforcement Learning + Imitation Learning based approach to AI Driving Olympics

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Longitudinal and lateral controllers for autonomous vehicles. Features PID and enhanced Stanley controllers. Implementation is for CARLA simulator.

Github Profile README

Training autonomous vehicles with Augmented Random Search algorithm in the Carla driving simulator. Flatiron Capstone Project.

DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.

Unscented Kalman Filter and Normalized Innovation Squared evaluation

Identification of road surfaces and 12 different classes like speed bumps, paved, unpaved, markings, water puddles, potholes, etc.

Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications

vehicleDistanceAlert is a Python project that uses a YOLOv4-tiny object detection model to detect vehicles on the road and alert the driver if they are too close. The system can be used in real time videos from camera. For simulation purpose pre-recorded videos are used. It is designed to be used in self-driving cars or other applications.

A simple self-driving car application with a neural network model.

Website for the ECC 2022 paper titled "Learning Eco-Driving Strategies at Signalized Intersections"

Stereo depth estimation for self-driving cars 🚗

An Intelligent Modular Real-Time Vision-Based System for Environment Perception (NeurIPS 2022 Workshop)