{
  "$type": "site.standard.document",
  "description": "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…",
  "path": "/patents/1291777",
  "publishedAt": "2021-06-03T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60W60/001",
    "Toyota Research Institute, Inc."
  ],
  "textContent": "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, Z. The GAN enforces Zto 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.",
  "title": "METHODS AND SYSTEMS FOR DIVERSITY-AWARE VEHICLE MOTION PREDICTION VIA LATENT SEMANTIC SAMPLING"
}