公开(公告)号：EP4414959A1

公开(公告)日：2024-08-14

申请号：EP23155609.3

申请日：2023-02-08

Applicant: Autoliv Development AB

Inventor： Alkhoury, Ziad ,  Ahmed, Jawwad

IPC: G08B21/04 ,  A61B5/11 ,  G16H50/30

CPC classification number: G08B21/0446 ,  A61B5/1117 ,  G16H50/30 ,  G16H50/70 ,  G16H50/20 ,  G16H40/63 ,  G16H40/67 ,  G08B29/186

Abstract: The present disclosure relates to a computer-implemented method for training of machine learning models in person accident event assessment. The method comprises preparing (S200) training data, by obtaining and automatically acquiring (S210) sensor data generated from sensors (2, 3; 6, 7) at an initial group (200) of subjects (201a-201c), and dividing (S220) the group (200) of subjects (201a-201c) into sub-groups (200a-200h) associated with certain corresponding features that are unique for the subjects (201a-201c) in that sub-group (200a-200h). The method further comprises training (S400) an initial machine learning model for the subjects in the initial group (200) and training (S500) a plurality of machine learning sub-models for the subjects (201a-201c) in the corresponding sub-group (200a-200h), such that one machine learning sub-model for each sub-group (200a-200h) is obtained.

公开(公告)号：EP4414222A1

公开(公告)日：2024-08-14

申请号：EP23155637.4

申请日：2023-02-08

Applicant: Autoliv Development AB

Inventor： Ahmed, Jawwad ,  Alkhoury, Ziad

IPC: B60R21/013 ,  G06N3/045

CPC classification number: B60R21/013

Abstract: The present disclosure relates to a computer-implemented method for training of a machine learning model in vehicle accident event assessment. The method comprises implementing (S100) the machine learning model, and preparing (S200) training data by obtaining and automatically acquiring (S210) sensor data generated from vehicle sensors (2, 3; 4, 5). The method further comprises applying data augmentation on the collected data to artificially increase the amount of collected data acquired from each sensor such that an augmented data set is acquired for each sensor.
For each sensor (2, 3; 4, 5), applying data augmentation (5220) comprises transforming (S221) the collected data to apply to a plurality of different sensor mounting positions and/or a plurality of different sensor mounting orientations within a certain sensor mounting area (6, 7), such that a further data set is obtained, the augmented data set comprising the collected data and the further data set. The method further comprises training (S300) the machine learning model using the augmented data set for each sensor (2, 3; 4, 5).