Speed profile planning for autonomous vehicle in dynamic environments over a fixed path

Autonomous Vehicle Control System using A* pathfinding, sensor data integration, and YOLO object detection in AirSim.

OpenPodCar_V2: Open source Hardware and Software platform for autonomous driving applications.

The Fifth Driver is a project for the Adaptative Computing Developer Contest for Xilinx. We pretend to demonstrate that the Xilinx Ultrascale+ MPSoC architecture is suitable for developing machine learning applications applied to Autonomous Driving.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning for Autonomous Driving leverages neural networks to analyze sensor data, detect objects, and support real-time driving decisions for safe and intelligent self-driving vehicles.

Adaptive_detection is a sophisticated reinforcement learning framework designed for autonomous driving applications using the CARLA simulator. The project integrates state-of-the-art YOLOv9 object detection to enable adaptive perception and decision-making in complex driving scenarios.