A unified boundary machine learning model is capable of processing perception data received from various types of perception sensors on an autonomous vehicle to generate perceived boundaries of various semantic boundary types. Such perceived boundaries may then be used, for example, to control the autonomous vehicle, e.g., by generating a trajectory therefor. In some instances, the various semantic boundary types detectable by a unified boundary machine learning model may include at least a virtual construction semantic boundary type associated with a virtual boundary formed by multiple spaced apart construction elements, as well as an additional semantic boundary type associated with one or more other types of boundaries such as boundaries defined by physical barriers, painted or taped lines, road edges, etc.
UNIFIED BOUNDARY MACHINE LEARNING MODEL FOR AUTONOMOUS VEHICLES
2025-03-06
Patent
Electronic Resource
English
IPC: | G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion |
UNIFIED BOUNDARY MACHINE LEARNING MODEL FOR AUTONOMOUS VEHICLES
European Patent Office | 2025
|UNIFIED BOUNDARY MACHINE LEARNING MODEL FOR AUTONOMOUS VEHICLES
European Patent Office | 2025
|A UNIFIED EVALUATION FRAMEWORK FOR AUTONOMOUS DRIVING VEHICLES
British Library Conference Proceedings | 2020
|