←All projects
Autonomous Vehicle Simulator Using Reinforcement Learning
Service
Custom AI Development
Delivered by
ZATNav
ZATNav built a simulated environment for testing, training, and validating autonomous vehicles, using the Unity 3D game engine alongside machine learning and AI algorithms.
Testing autonomous vehicle behavior in the real world is expensive, slow, and risky before the system has been proven safe. Teams need a way to validate driving behavior without putting a physical vehicle on the road.
ZATNav’s team built a prototype simulator where a virtual vehicle learns to drive on its own using deep reinforcement learning and Convolutional Neural Networks (CNNs). Unity 3D generates the driving environment and sends state data to a Python-based CNN, which processes it and sends control commands back to the simulated vehicle.
A working prototype that gives teams a cost-effective, repeatable way to test autonomous driving behavior before moving to real-world trials.
AI model development, reinforcement learning, simulation environment design.