Visualizations of algorithms covered in Sebastian Thrun's excellent Artificial Intelligence for Robotics course on Udacity.

Use segmentation networks to recognize lane lines and vehicles. Infer position and curvature of lane lines relative to self.

Entire Self-Driving Car Software Stack Tested on Real Vehicle

ROS-based code to control a real self-driving car. Final project for "Wolf Pack" team in Udacity's Self-Driving Car Engineer Nanodegree.

Pytorch model (CNN) to drive a simulated car autonomously in the Udacity Self-Driving Car Simulation.

Self driving car running over udacity's "unity car simulator" using Convolutional neural networks.

An experimental project for autonomous vehicle driving perception with steering angle prediction and semantic segmentation using a combination of UNet, attention and transformers.

End-to-End Deep Learning for Self-Driving Cars

Won 28th place in this competition to accurately detect cars and road in images from CARLA simulator at 10 frames per second.

This project is my implementation of NVIDIA's PilotNet End to End deep CNN (built with Keras) to clone the behavior of a self driving car .

Self driving car capstone project based on ROS and light-weight traffic light detection CNN model

In this project CNN model is cloning human style of steering control. This is an assignment of Self Driving Car Engineer nano degree course offered by Udacity.

My Submission for Udacity Self Driving Car Nano Degree Behavioral Cloning Project

Udacity Self-Driving Car Nanodegree: Vehicle Detection Project

This project demonstrate basic self driving car model using udacity car driving simulator

Self Driving Car ND Project 3 - Behavioral Cloning

SmartCarla

Train a self-driving car to mimic examples of human driving

Python script to detect vehicles from an image for self-driving purpose

Pixel wise semantic segmentation for highway roads using FCN-8 architecture