Training algorithm for collision avoidance using auditory data
US10055675B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 15, 2016 |
| Grant date | Aug 21, 2018 |
| Priority date | — |
| Expiry date | Sep 17, 2036 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T90/00
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A machine learning model is trained by defining a scenario including models of vehicles and a typical driving environment. A model of a subject vehicle is added to the scenario and sensor locations are defined on the subject vehicle. A perception of the scenario by sensors at the sensor locations is simulated. The scenario further includes a model of a parked vehicle with its engine running. The location of the parked vehicle and the simulated outputs of the sensors perceiving the scenario are input to a machine learning algorithm that trains a model to detect the location of the parked vehicle based on the sensor outputs. A vehicle controller then incorporates the machine learning model and estimates the presence and/or location of a parked vehicle with its engine running based on actual sensor outputs input to the machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.