Lane Merging and Fork Area Segmentation Dataset

Welcome to the fascinating world of autonomous driving, powered by our rich and diverse datasets. These datasets, meticulously curated and annotated, are the lifeblood of the self-driving car industry, fueling advancements across various domains.

The "Lane Merging and Fork Area Segmentation Dataset" specifically addresses the complexities of lane merging and forking, critical scenarios in autonomous driving. This dataset, consisting of driving recorder images, is annotated for binary segmentation, focusing on areas where lanes merge or branch off. It includes detailed labels for lane merging areas, lane fork areas (marked by triangular inverted lines), and potential obstructions such as vehicles, trees, road signs, and pedestrians. This dataset is a vital tool for training AI models to navigate these challenging road situations, ensuring smoother and safer autonomous driving experiences.