Method of effective driving behavior extraction using deep learning
US10198693B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 24, 2016 |
| Grant date | Feb 5, 2019 |
| Priority date | — |
| Expiry date | Feb 18, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for obtaining vehicle operational data and driving context data from one or more monitoring systems, including converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data, calibrating the sequential vehicle operational feature data and the sequential driving context feature data temporally to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data, constructing a sequence table of temporal sample points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data, feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model, extracting driving behavior features from the trained deep neural network model and analyzing the extracted driving behavior features to determine driving behavior characteristics of the driver.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.