In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver’s maneuver intentions offers opportunities to improve driving experience and safety. Especially brake maneuvers are of fundamental importance because they are directly related to the avoidance of potential hazards.Current state-of-the-art brake assistance systems rely on the release speed of accelerator pedal as an indicator whether a brake event is planned. However, this simple and practical algorithm, fails to capture the overall movement pattern of accelerator pedal behaviors and cannot utilize rich information from different vehicle sensors.To address this issue, we propose a novel recurrent neural network architecture for the purpose of brake maneuver prediction. The proposed method exploits the advantages of multiple sensors. Unlike conventional practices where all signals are aggregated to a single neural network, we leverage the confidence of each sensor. We evaluate our approach based on a dataset of 44 drivers, comprising around 500 hours of naturalistic driving data. The evaluation results show that the proposed algorithm outperforms baseline method by large margin.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Brake Maneuver Prediction – An Inference Leveraging RNN Focus on Sensor Confidence


    Contributors:
    Liu, Shu (author) / Koch, Kevin (author) / Gahr, Bernhard (author) / Wortmann, Felix (author)


    Publication date :

    2019-10-01


    Size :

    1142895 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Leveraging sensor information from portable devices towards automatic driving maneuver recognition

    Sathyanarayana, Amardeep / Sadjadi, Seyed Omid / Hansen, John H.L. | IEEE | 2012


    Leveraging GPS Data for Vehicle Maneuver Detection

    Aymen, Abdallah / Imen, Jemili / Sabra, Mabrouk et al. | British Library Conference Proceedings | 2020


    Virtual Brake Pull Maneuver Development

    Terra, Rafael Tedim | SAE Technical Papers | 2024


    GEO spacecraft maneuver detection based on causal inference

    Long, Xi / Leping, Yang / Weiwei, Cai et al. | Elsevier | 2023


    Maneuver prediction for surrounding traffic

    SINDLINGER ANDREAS / PARRA GAROE GONZALEZ / SCHULZE JONAS MICHAEL | European Patent Office | 2019

    Free access