Deep learning based beam control for autonomous vehicles

Provided are systems and methods for a deep learning based beam control. Sensor data associated with the environment and the corresponding detected objects from a perception system are obtained. Object features and image features are extracted. The extracted object features and image features are fu...

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Bibliographic Details
Main Authors Karan Rajendra Shetti, Xiaoli Meng, Lubing Zhou
Format Patent
LanguageEnglish
Published 14.08.2024
Subjects
ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING ORSUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES INGENERAL
BLASTING
CALCULATING
COMPUTING
COUNTING
HEATING
LIGHTING
MECHANICAL ENGINEERING
NON-PORTABLE LIGHTING DEVICES
PERFORMING OPERATIONS
PHYSICS
SYSTEMS THEREOF
TRANSPORTING
VEHICLE LIGHTING DEVICES SPECIALLY ADAPTED FOR VEHICLEEXTERIORS
VEHICLES IN GENERAL
WEAPONS
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Summary:Provided are systems and methods for a deep learning based beam control. Sensor data associated with the environment and the corresponding detected objects from a perception system are obtained. Object features and image features are extracted. The extracted object features and image features are fused into fused features. A beam control status is predicted according to the fused features, wherein the beam control status indicates a high beam illumination intensity or a low beam illumination intensity of a light emitting device.
Bibliography:Application Number: GB20220000408