self-driving-cars

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

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

A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.

End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)

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

Motion Planner for Self Driving Cars

Vehicle Detection with Convolutional Neural Network

Cooperative Driving Dataset: a dataset for multi-agent driving scenarios

Convolutional Neural Network for German Traffic Sign Recognition Benchmark

Path planning implemented with behavior trees

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

Self-driving AI toy car 🤖🚗.

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

Semantic Understanding of Foggy Scenes with Purely Synthetic Data

My 10 takeaways from the 2019 Intelligent Vehicle Symposium

[IEEE RAL] Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications

Rich literature review and discussion on the implementation of "Hierarchical Decision-Making for Autonomous Driving"

Stereo depth estimation for self-driving cars 🚗

Intelligent Driver Monitoring system for Autonomous Vehicles

Motion Control of Self-Driving Car for Trajectory Tracking