Method and system for analyzing and predicting vehicle stay behavior based on multi-task learning
US12118832B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 23, 2023 |
| Grant date | Oct 15, 2024 |
| Priority date | — |
| Expiry date | Oct 23, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/04
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
The present application discloses a method and a system for analyzing and predicting a vehicle stay behavior based on multi-task learning, and the method includes the following steps: acquiring vehicle GPS and OBD data including a vehicle ID, a travel start time, a start longitude, a start latitude, an end time, an end longitude, and an end latitude after desensitization; preprocessing vehicle GPS and OBD data to obtain vehicle stay behavior data including stay location and stay duration; extract a spatial-temporal characteristic of the preprocessed vehicle stay behavior data by a deep recurrent neural network; inputting the spatial-temporal characteristic into a multi-task learning and predicting network, and obtaining the correlation between a stay location prediction task and the stay duration prediction task based on the historical stay behavior of the vehicle through the multi-task learning and predicting network to predict the stay location and stay duration.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.