Methods and systems for diversity-aware vehicle motion prediction via latent semantic sampling
US11654934B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 25, 2020 |
| Grant date | May 23, 2023 |
| Priority date | — |
| Expiry date | Oct 8, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method for generating a predicted vehicle trajectory includes a generative adversarial network configured to receive a trajectory vector of a target vehicle and generate a set of latent state vectors using the received trajectory vector and an artificial neural network. The latent state vectors each comprise a high-level sub-vector, ZH. The GAN enforces ZH to be correlated to an annotation coding representing semantic categories of vehicle trajectories. The GAN selects a subset, from the set of latent state vectors, using farthest point sampling and generates a predicted vehicle trajectory based on the selected subset of latent state vectors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.