dragonpilot - 基於 openpilot 的開源駕駛輔助系統

An open source advanced driver assistance system (ADAS) that uses Jetson Nano as the hardware. Features: Traffic sign detection, Forward collision warning, Lane departure warning.

Learn to map surrounding vehicles onto a bird's eye view of the scene.

Openpilot on Jetson Xavier NX

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

A powerful open environment for automotive bus monitoring, simulation, testing, diagnostics, calibration and so on. It supports all kinds of mainstream hardware such as TOSUN, Vector, IXXAT, PEAK, Kvaser, Intrepidcs, ZLG, CANable, CandleLight, cantact and so on. Free for research and education purpose for some features.

A project to demonstrate lane detection with a front facing camera.

Implementation of "A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application"

[TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural network learnt to reproduce the human driver focus of attention (FoA) in a variety of real-world driving scenarios.

ANOTHER openpilot fork running on legacy devices (EON / LEON / comma two)

YOLOv8-3D is a LowCode, Simple 2D and 3D Bounding Box Object Detection and Tracking , Python 3.10

Collision Avoidance System for Self-Driving Vehicles by Delta Autonomy, Robotics Institute, CMU

🚚 ETSAuto is an Advanced driver Assistance System applied in Euro Truck Simulator 2, performing the functions of Lane Centering Control (LCC) and Auto Lane Change (ALC).

Lane identification system for camera based systems.

Automatic Parking is an autonomous car maneuvering system (part of ADAS) that moves a vehicle from a traffic lane into a parking spot to perform parallel parking. The automatic parking system aims to enhance the comfort and safety of driving in constrained environments where much attention and experience is required to steer the car. The parking…

Lane depertaure and Yolo objection detection C++ Linux

Implementation of the Automatic Emergency Braking System using deep learning.

Graduation project repository, Real-time vehicle detection using two different approaches. HOG+SVM traditional approach and Deep Learning based approach using state of the art YOLO convolutional neural network.

TSMaster Demo Program Source Code