The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a machine-learned yield model. In particular, the machine-learned yield model can be trained or otherwise configured to receive and process feature data descriptive of objects perceived by the autonomous vehicle and/or the surrounding environment and, in response to receipt of the feature data, provide yield decisions for the autonomous vehicle relative to the objects. For example, a yield decision for a first object can describe a yield behavior for the autonomous vehicle relative to the first object (e.g., yield to the first object or do not yield to the first object). Example objects include traffic signals, additional vehicles, or other objects. The motion of the autonomous vehicle can be controlled in accordance with the yield decisions provided by the machine-learned yield model.
Autonomous vehicles featuring machine-learned yield model
2018-07-10
Patent
Elektronische Ressource
Englisch
IPC: | G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS / 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 / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
Autonomous vehicles featuring machine-learned yield model
Europäisches Patentamt | 2021
|Autonomous vehicles featuring machine-learned yield model
Europäisches Patentamt | 2023
|Autonomous Vehicles Featuring Machine-Learned Yield Model
Europäisches Patentamt | 2022
|Autonomous vehicles featuring vehicle intention system
Europäisches Patentamt | 2022
|Autonomous Vehicles Featuring Vehicle Intention System
Europäisches Patentamt | 2020
|