Driving scenario sampling for training/tuning machine learning models for vehicles
US11364927B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 9, 2021 |
| Grant date | Jun 21, 2022 |
| Priority date | — |
| Expiry date | Jul 9, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Enclosed are embodiments for sampling driving scenarios for training machine learning models. In an embodiment, a method comprises: assigning, using at least one processor, a set of initial physical states to a set of objects in a map for a set of simulated driving scenarios, wherein the set of initial physical states are assigned according to one or more outputs of a random number generator; generating, using the at least one processor, the set of simulated driving scenarios in the map using the initial physical states of the objects in the set of objects; selecting, using the at least one processor, samples of the simulated driving scenarios; training, using the at least one processor, a machine learning model using the selected samples; and operating, using a control circuit, a vehicle in an environment using the trained machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.