{
  "$type": "site.standard.document",
  "description": "An autonomous vehicle uses machine learning based models to predict hidden context attributes associated with traffic entities. The system uses the hidden context to predict behavior of people near a vehicle in a way that more closely resembles how human drivers would judge the behavior. The system…",
  "path": "/patents/1268506",
  "publishedAt": "2020-07-30T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G05D1/0221",
    "Perceptive Automata, Inc."
  ],
  "textContent": "An autonomous vehicle uses machine learning based models to predict hidden context attributes associated with traffic entities. The system uses the hidden context to predict behavior of people near a vehicle in a way that more closely resembles how human drivers would judge the behavior. The system determines an activation threshold value for a braking system of the autonomous vehicle based on the hidden context. The system modifies a world model based on the hidden context predicted by the machine learning based model. The autonomous vehicle is safely navigated, such that the vehicle stays at least a threshold distance away from traffic entities.",
  "title": "AUTOMATIC BRAKING OF AUTONOMOUS VEHICLES USING MACHINE LEARNING BASED PREDICTION OF BEHAVIOR OF A TRAFFIC ENTITY"
}