{
  "$type": "site.standard.document",
  "description": "Systems and methods for testing a machine learning algorithm or technique of an autonomous driving feature of a vehicle utilize a sensor system configured to capture input data representative of an environment external to the vehicle and a controller configured to receive the input data from the…",
  "path": "/patents/1316230",
  "publishedAt": "2022-04-28T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60W50/06",
    "Neil Garbacik"
  ],
  "textContent": "Systems and methods for testing a machine learning algorithm or technique of an autonomous driving feature of a vehicle utilize a sensor system configured to capture input data representative of an environment external to the vehicle and a controller configured to receive the input data from the sensor system and perform a testing procedure for the autonomous driving feature that includes inserting known input data into a target portion of the input data to obtain modified input data, processing the modified input data according to the autonomous driving feature to obtain output data, and determining an accuracy of the autonomous driving features based on a comparison between the output data and the known input data.",
  "title": "FUNCTIONALLY SAFE RATIONALIZATION CHECK FOR AUTONOMOUS VEHICLE MACHINE LEARNING ALGORITHMS"
}