Autonomous vehicle model training and validation using low-discrepancy sequences
US11958500B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 24, 2023 |
| Grant date | Apr 16, 2024 |
| Priority date | — |
| Expiry date | Mar 24, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/214
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Autonomous vehicle model training and validation using low-discrepancy sequences may include: generating a low-discrepancy sequence in a multidimensional space comprising a plurality of multidimensional points; mapping each sample of a plurality of samples of a data corpus to a corresponding entry in the low-discrepancy sequence, wherein each sample of the plurality of samples comprises one or more environmental descriptors for an environment relative to a vehicle and one or more state descriptors describing a state of the vehicle; selecting, from the data corpus, a training data set by selecting, for each multidimensional point of the low-discrepancy sequence having one or more mapped samples, a mapped sample for inclusion in the training data set; and training one or more models used to generate autonomous driving decisions of an autonomous vehicle based on the selected training data set.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.