Algorithm that steers a vehicle by using just the front-facing camera as an input feed (Advance lane detection)
This project introduces the autonomous robot which is a scaled down version of actual self-driving vehicle and designed with the help of neural network. The main focus is on building autonomous robot and train it on a designed track with the help of neural network so that it can run autonomously without a controller or driver on that specific tr…
Formula Student Driverless Simulator Rust API.
Using deep learning and Convolutional Neural Networks to train a driverless vehicle and use of socket.io and Flask to for real time data communication to simulate the vehicle in a simulator
Advanced Autonomous Vehicle Simulation
UDS (Udacity Driverless System) is an autonomous driving project developed using deep learning techniques and socket communication with a simulator. It was developed as an internship project during my internship at Zhilin Information Technology Co., Ltd., organized by Taiyuan University of Technology and the company itself, in 10.04.2024-23.04.2024
AI DriverLess Car is a high performance, flexible architecture which accelerates the development, testing, and deployment of Autonomous Vehicles.
In this project , Car lanes are detected on a sample road video & image by using opencv_techniques and concepts
A real-time Advanced Driver Assistance System (ADAS) perception stack built with Python. Features object detection, lane tracking, and driver monitoring, optimized for unstructured traffic environments (Indian Roads).
Reinforcement Learning for Autonomous Driving
Add a description, image, and links to the driverless-car topic page so that developers can more easily learn about it.
To associate your repository with the driverless-car topic, visit your repo's landing page and select "manage topics."