Neural network with lane aggregation for lane selection prediction of moving objects during autonomous driving
US11663913B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 1, 2019 |
| Grant date | May 30, 2023 |
| Priority date | — |
| Expiry date | Jan 28, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/24317
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, an autonomous driving system of an ADV perceives a driving environment surrounding the ADV based on sensor data obtained from various sensors, including detecting one or more lanes and at least a moving obstacle or moving object. For each of the lanes identified, an NN lane feature encoder is applied to the lane information of the lane to extract a set of lane features. For a given moving obstacle, an NN obstacle feature encoder is applied to the obstacle information of the obstacle to extract a set of obstacle features. Thereafter, a lane selection predictive model is applied to the lane features of each lane and the obstacle features of the moving obstacle to predict which of the lanes the moving obstacle intends to select.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.