Machine-learning based control of traffic operation
US12020566B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 20, 2022 |
| Grant date | Jun 25, 2024 |
| Priority date | — |
| Expiry date | May 20, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G1/096775
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A method of modifying or controlling a highway traffic system may include training a machine learning model using historical traffic data corresponding to a roadway traffic system in which the historical traffic data is indicative of traffic patterns over a historical time interval. The method may include obtaining, by the machine learning model, traffic data corresponding to the roadway traffic system and determining a probability of traffic congestion occurrence based on the obtained traffic data corresponding to the roadway traffic system. The method may include comparing the probability of traffic congestion occurrence to a traffic control probability threshold, and responsive to the probability of traffic congestion exceeding the traffic control probability threshold, adjusting operations associated with one or more traffic controls that correspond to the roadway traffic system. The machine learning model may be retrained after a time interval using the obtained traffic data corresponding to the roadway traffic system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.