Using brain signals rather than limbs to drive a vehicle may not only help persons with disabilities to acquire driving ability, but also provide a new alternative interface for healthy people to control a vehicle. However, the longitudinal driving performance of brain-controlled vehicles (BCVs) at a relatively high speed is not good enough. In this paper, to improve the performance of the longitudinal brain-control driving, we propose a new predictive control method based on the models of human behaviors and vehicle dynamics. The proposed method is designed to maintain rear-end safety of BCVs and driver ride comfort while ensuring the maximum control authority of brain-control drivers. Driver-and-hardware-in-the-loop experiments are conducted with different subjects under three kinds of scenarios to validate the proposed method. The results show that the proposed method is effective in maintaining rear-end safety and driver ride comfort while preserving driver intention.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Human Behavior Model-Based Predictive Control of Longitudinal Brain-Controlled Driving


    Beteiligte:
    Lu, Yun (Autor:in) / Bi, Luzheng (Autor:in)


    Erscheinungsdatum :

    01.03.2021


    Format / Umfang :

    3325350 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Model Predictive-Based Shared Control for Brain-Controlled Driving

    Lu, Yun / Bi, Luzheng / Li, Hongqi | IEEE | 2020


    Model Predictive Longitudinal Control for Autonomous Driving

    Dahiwale, Priyanka B. / Chaudhari, Madhuri A. / Kumar, Rohit et al. | IEEE | 2023



    AN EXPERIMENTAL STUDY ON LONGITUDINAL DRIVING ASSISTANCE BASED ON MODEL PREDICTIVE CONTROL

    Okuda, H. / Tazaki, Y. / Suzuki, T. et al. | British Library Conference Proceedings | 2013


    An experimental study on longitudinal driving assistance based on model predictive control

    Okuda, Hiroyuki / Tazaki, Yuichi / Suzuki, Tatsuya | IEEE | 2013