公开(公告)号：WO2023059868A1

公开(公告)日：2023-04-13

申请号：PCT/US2022/046020

申请日：2022-10-07

Applicant: NEC LABORATORIES AMERICA, INC.

Inventor： TANG, LuAn ,  CHEN, Yuncong ,  CHENG, Wei ,  CHEN, Zhengzhang ,  CHEN, Haifeng ,  KOBAYASHI, Yuji ,  REN, Yuxiang

IPC: G06N3/08 ,  G06N3/04 ,  G06N7/00 ,  B60W2420/42 ,  B60W2540/30 ,  B60W40/09 ,  G06F18/25 ,  G06N3/084

Abstract: Systems and methods for data fusion and analysis of vehicle sensor data, including receiving a multiple modality input data stream from a plurality of different types of vehicle sensors, determining latent features by extracting modality-specific features from the input data stream, and aligning a distribution of the latent features of different modalities by feature-level data fusion. Classification probabilities can be determined for the latent features using a fused modality scene classifier. A tree-organized neural network can be trained to determine path probabilities and issue driving pattern judgments, with the tree-organized neural network including a soft tree model and a hard decision leaf. One or more driving pattern judgments can be issued based on a probability of possible driving patterns derived from the modality-specific features.

公开(公告)号：WO2023086533A1

公开(公告)日：2023-05-19

申请号：PCT/US2022/049646

申请日：2022-11-11

Applicant: NEC LABORATORIES AMERICA, INC.

Inventor： TANG, LuAn ,  CHEN, Yuncong ,  CHENG, Wei ,  CHEN, Haifeng ,  CHEN, Zhengzhang ,  KOBAYASHI, Yuji

IPC: B60W50/02 ,  B60W50/00 ,  B60W60/00 ,  B60W40/02 ,  G07C5/08

Abstract: Systems and methods for defect detection for vehicle operations, including collecting a multiple modality input data stream from a plurality of different types of vehicle sensors, extracting one or more features from the input data stream using a grid-based feature extractor, and retrieving spatial attributes of objects positioned in any of a plurality of cells of the grid-based feature extractor. One or more anomalies are detected based on residual scores generated by each of cross attention-based anomaly detection and time-series-based anomaly detection. One or more defects are identified based on a generated overall defect score determined by integrating the residual scores for the cross attention-based anomaly detection and the time-series based anomaly detection being above a predetermined defect score threshold. Operation of the vehicle is controlled based on the one or more defects identified.

公开(公告)号：WO2022055783A1

公开(公告)日：2022-03-17

申请号：PCT/US2021/048817

申请日：2021-09-02

Applicant: NEC LABORATORIES AMERICA, INC. ,  NEC CORPORATION

Inventor： TANG, LuAn ,  CHENG, Wei ,  CHEN, Haifeng ,  KOBAYASHI, Yuji ,  CHEN, Zhengzhang

IPC: G06F11/20 ,  G06F11/22 ,  G06F11/30 ,  G06N3/08 ,  B60K35/00

Abstract: A method for early warning is provided. The method clusters (810) normal historical data of normal cars into groups based on the car subsystem to which they belong. The method extracts (820) (i) features based on group membership and (ii) feature correlations based on correlation graphs formed from the groups. The method trains (830) an Auto-Encoder and Auto Decoder (AE&AD) model based on the features and the feature correlations to reconstruct the normal historical data with minimum reconstruction errors. The method reconstructs (840), using the trained AE&AD model, historical data of specific car fault types with reconstruction errors, normalizes the reconstruction errors, and selects features of the car faults with a top k large errors as fault signatures. The method reconstructs (850) streaming data of monitored cars using the trained AE&AD model to determine streaming reconstruction errors, comparing the streaming reconstruction errors with the fault signatures to predict and provide alerts for impending known faults.