End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)
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Updated
May 14, 2020 - Python
End-to-end Lane Detection for Self-Driving Cars (ICCV 2019 Workshop)
Vehicle Detection with Convolutional Neural Network
Motion Planner for Self Driving Cars
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
Intelligent Driver Monitoring system for Autonomous Vehicles
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Using OpenCV to detect Lane Lines on a road, one of the most fundamental concepts for building a Self-Driving car.
Stereo depth estimation for self-driving cars 🚗
A macroscopic multivehicle tesbed and hardware-in-the-loop simulator for autonomous driving
Behavioral Cloning Project for Self-Driving Car Nano Degree Term 1. The project includes designing a neural network and then training the car on the road in unity simulator. The CNN learns and clones the driving behavior.
Motion Control of Self-Driving Car for Trajectory Tracking
We provide the code, pretrained models, and scripts to reproduce the experiments of the paper "Towards All-Weather Autonomous Driving". All code was implemented in Python using the deep learning framework PyTorch.
To ease the driver to identify the Traffic Signs and also for the efficient working of Self-Driving Cars.
A CNN built with Keras and trained to predict steering angles from camera input
Fast and Robust Registration of Partially Overlapping Point Clouds in Driving Applications
a fuzzy distance controller for a following vehicle in a bidirectional movement space. This is a simple test to demonstrate the mechanics of such a controller. The driving behaviour and the current distance are taken into account. Further components can be easily added. The output variable is the adjustment of the speed.
This work consists of designing a miniature autonomous car that can follow a road, detect signalisations and obstacles.
Semantic Segmentation project for Autonomous Driving based on a TensorFlow implementation of UNet
A tool for predicting unsafe road scenarios for self-driving cars in BeamNG.tech.
A practical implementation of pixel level segmentation based road detection and steering angle estimation methods.
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