DYNAMICALLY WEIGHTING TRAINING DATA USING KINEMATIC COMPARISON

The present disclosure generally relates to autonomous vehicle (AV) prediction systems and in particular, to novel methods for training a prediction layer of the AV software stack. In some aspects, the disclosure can provide a process for receiving road data representing a plurality of entities, pre...

Full description

Saved in:
Bibliographic Details
Main Authors Lazarovici, Allan, Xie, Bo, Elkherj, Matthew
Format Patent
LanguageEnglish
Published 26.09.2024
Subjects
CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION
CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES
PERFORMING OPERATIONS
ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT
TRANSPORTING
VEHICLES IN GENERAL
Online AccessGet full text

Cover

More Information
Summary:The present disclosure generally relates to autonomous vehicle (AV) prediction systems and in particular, to novel methods for training a prediction layer of the AV software stack. In some aspects, the disclosure can provide a process for receiving road data representing a plurality of entities, predicting, using a prediction layer of an autonomous vehicle (AV), a first set of future trajectories for one or more of the plurality of entities, and predicting, using a kinematics model, a second set of future trajectories for one or more of the plurality of entities. In some approaches, the process can further include steps for flagging one or more instances in the road data for which the first set of future trajectories is less accurate than the second set of future trajectories. Systems and machine-readable media are also provided.
Bibliography:Application Number: US202318187509