Multi-objective bayesian optimization of machine learning model for autonomous vehicle operation
US12128923B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 9, 2022 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Feb 7, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine learning model optimization systems and methods are disclosed. A system receives sensor data captured by one or more sensors of a vehicle during a first time period. The vehicle uses a first trained machine learning (ML) model for one or more decisions of a first decision type during the first time period. The system generates a second trained ML model at least in part by using the sensor data to train the second trained ML model. The system identifies an optimal trained ML model from a plurality of trained ML models. The plurality of trained ML models includes the first trained ML model and the second trained ML model. The system causes the vehicle to use the optimal trained ML model for one or more further decisions of the first decision type during a second time period after the first time period.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.