Autonomous vehicles featuring machine-learned yield model
US10019011B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 24, 2017 |
| Grant date | Jul 10, 2018 |
| Priority date | — |
| Expiry date | Oct 24, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G1/166
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.