Autonomous Driving Simulator

We developed a cutting-edge web application designed to manage, analyze, and simulate data for autonomous driving systems. The platform automated the extraction of driving scenarios from raw sensor data, managed complex datasets, and provided a seamless interface for visualizing and customizing simulations.

Key features included the ability to process and categorize real-world driving data, detect and eliminate duplicate entries, and offer advanced search capabilities for quick scenario retrieval. The user-friendly interface allowed engineers to interact with the data efficiently, enhancing their workflow and decision-making process.

This solution significantly streamlined the management and utilization of autonomous driving data, ensuring greater accuracy, scalability, and ease of access for researchers and developers.

Technologies Used: Python, CARLA Simulator, Google Cloud Platform (GCP), and Unreal Engine.