Structural object detector for hierarchical ontology for traffic light handling

Abstract

Systems and methods are provided for developing/leveraging a hierarchical ontology in traffic light perception. A hierarchical ontology representative of various traffic light characteristic (e.g., states, transitions, colors, shapes, etc.) allow for structured and/or automated annotation (in supervised machine learning), as well as the ability to bootstrap traffic light prediction. Further still, the use of a hierarchical ontology provides the ability to accommodate both coarse and fine-grained model prediction, as well as the ability to generate models that are applicable to different traffic light systems used, e.g., in different geographical regions and/or contexts.