By way of example, the technology disclosed by this document may be implemented in a method that includes receiving stored sensor data describing characteristics of a vehicle in motion at a past time and extracting features for prediction and features for recognition from the stored sensor data. The features for prediction may be input into a prediction network, which may generate a predicted label for a past driver action based on the features for prediction. The features for recognition may be input into a recognition network, which may generate a recognized label for the past driver action based on the features for recognition. In some instances, the method may include training prediction network weights of the prediction network using the recognized label and the predicted label.


    Access

    Download


    Export, share and cite



    Title :

    Efficient driver action prediction system based on temporal fusion of sensor data using deep (bidirectional) recurrent neural network


    Contributors:

    Publication date :

    2021-09-14


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS



    Driver Action Prediction Using Deep (Bidirectional) Recurrent Neural Network

    Olabiyi, Oluwatobi / Martinson, Eric / Chintalapudi, Vijay et al. | ArXiv | 2017

    Free access

    Sensor data reconstruction and anomaly detection using bidirectional recurrent neural network

    Jeong, Seongwoon / Ferguson, Max / Law, Kincho H. | British Library Conference Proceedings | 2019




    ENHANCED MULTI-SENSOR DATA FUSION METHOD USING RECURRENT NEURAL NETWORK

    He, Jing / Guo, Chengjun / Tao, Chao | TIBKAT | 2021