Autonomous vehicles process terabytes of data every day, but this flood of sensor data does not account for the complexity of the real-world environment. Combining spatial depth with time-based tracking redefines environmental analysis. By incorporating temporal layers into 3D mapping, systems can now predict pedestrian movement more accurately and efficiently