Lane graph generation using neural networks

This invention describes a system that uses sensor data from multiple self-driving vehicles to create detailed maps of road lanes. It works by dividing the road into a grid, then using artificial intelligence to identify lane cross-sections within each grid cell based on the combined sensor data. These identified cross-sections are then assembled to generate a complete map of the lanes and their dividers for autonomous navigation.

Why it matters: Filed just two years ago, rapid advancements in neural network architectures and multi-vehicle sensor fusion techniques could make building this system more efficient and robust now. Specifically, improvements in graph neural networks might simplify generating the lane graph from diverse sensor inputs.

Status: Under examinationA pending application. It has not been granted, and it has not been abandoned.
How hard to build: SpecializedNeural networks, sensor fusion, complex software

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