Cognitive-based driving anomaly detection based on spatio-temporal landscape-specific driving models
US10252461B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 27, 2017 |
| Grant date | Apr 9, 2019 |
| Priority date | — |
| Expiry date | Mar 27, 2037 |
Classification
- Technology area (CPC B)Performing Operations; Transporting
- CPC primaryB29K2023/00
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
Methods, systems, and computer program products for driving anomaly detection based on spatio-temporal landscape-specific driving models are provided herein. A method includes generating, for each of multiple users, a temporally-related driving skill model pertaining to one or more landscapes, wherein the model is based on temporally-related driving data associated with the users and landscape-related information of trips driven by the users; monitoring the users participating in a ride-sharing trip in a vehicle by analyzing ride-sharing trip data; detecting driving-related anomalies attributed to the monitored users by comparing the ride-sharing trip data and the respective temporally-related driving skill model for each monitored user; updating a schedule for the trip based on the detected anomalies and estimated conditions attributed to remaining portions of the trip by modifying an assignment of selected users to drive the vehicle during the remaining portions of the trip; and outputting the updated schedule to the selected users.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.