There are 2 repositories under lane-tracking topic.
A collection of all projects pertaining to different layers in the SDC software stack
Lane and obstacle detection for active assistance during driving. Uses windowed sweep for lane detection. Combination of object tracking and YOLO for obstacles. Determines lane change, relative velocity and time to collision
we present the plans of a driver-assistance system, which will be capable of road lane and traffic sign detection by using an OPEN-CV.
Implementation of the Automatic Emergency Braking System using deep learning.
Autonomous Driving Simulator for the Portuguese Robotics Open
Virtual Lane Boundary Generation for Human-Compatible Autonomous Driving
Cross-platform Python based software in the loop simulation for object tracking and general quadcopter simulations using custom pure-Python based custom pure PID (and customisable) flight controller
Lane depertaure and Yolo objection detection C++ Linux
Particle filter-based lane tracking Matlab code
Self-driving vehicle with lane keeping functionality on a RPi 3B+.
Lane Detection and Departure warning.
Lane tracking was done from the images taken from the camera placed on top of the vehicles using Computer Vision. Not done yet.
This repo consists of details and open-sourced codes and materials of the HeRoCars - a Robotics Learning Technology developed at the Heterogeneous Robotics Lab of the University of Georgia. HeRoCars is a simulator-hardware integrative framework consisting of a game-inspired Unity-based Simulator module and a low-cost hardware module of robotized RC cars.
Lane Detection and Tracking project using opencv in python
Build a simple lane detector with Python and OpenCV
Distinguish lanes for self-driving cars- using color selection, region masking & edge detection
This repository contains my development of the Project: Advanced Lane Lines proposed by the Udacity's Self-Driving Cars Nanodegree
C++ Lane Detection using OpenCV
Finding Lane Lines on the Road (project 1 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
Udacity Self Driving Car Engineer Project - Advanced Lane Lines Detection
Goal is to create a software pipeline to identify the lane boundaries in a video and write a detailed commentary on the output.
Cheongju University Camera(OpenCV) Lecture
Our National Telecommunication Institute (NTI) ADAS CAR System. Its Features: 1-Lane Keeping ,2-Lane Changing ,3-Blind-Spot ,4-Emergency Break, 5- Adaptive Cruise Control, 6-Front Collision Avoidance ,7-Rear Collision Avoidance ,8- Right Side Collision Avoidance, 9-Left Side Collision Avoidance,10-Rain Detection+ Auto Wipers,11-Thief detection
This repository contains my development of the Project: Finding Lane Lines proposed by the Udacity's Self-Driving Cars Nanodegree
Lane Finding and Curvature Estimation using Advanced CV techniques
This is a very simple lane detection made with python.
Road Lane Lines finding through Color Selection
Lane Line detection is a critical component for self driving cars and also for computer vision in general. This concept is used to describe the path for self-driving cars and to avoid the risk of getting in another lane. In this repo, we will build a machine learning project to detect lane lines in real-time. We will do this using the concepts of computer vision using OpenCV library. To detect the lane we have to detect the white markings on both sides on the lane.