The automatic emergency braking system (AEB) of intelligent automobile is prone to false triggering or failure in curve environment. This paper presents a hierarchical AEB objective detection and predictive control methods under two typical curve conditions: curving road, turning into straight road. In the upper layer, a geometric curving compensation method is developed to detect the potential collision target in curving condition. Then, the inversed of Time To Collision (iTTC) and risk effective factor ( γ \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}) calculated based on the relative states of self-vehicle and potential target are used to determine the expected. A hybrid predictive control-based speed tracking algorithm is designed in the lower control layer, where the tire braking force characteristics are systematically analysed and the braking force model are converted into a mix logical force model to accommodate the tire force saturation situation. Finally, the co-simulation and car-like robot test are carried out to verify the feasibility and effectiveness of proposed strategy.


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    Titel :

    Effective Objective Detection and Hybrid Predictive Control for Intelligent Vehicle Automatic Emergency Braking Under Curving Road Scenario


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Bowen (Autor:in) / Lin, Cheng (Autor:in) / Gong, Xinle (Autor:in) / Liang, Sheng (Autor:in)

    Kongress:

    Society of Automotive Engineers (SAE)-China Congress ; 2022 ; Shanghai, China November 22, 2022 - November 24, 2022



    Erscheinungsdatum :

    2023-04-29


    Format / Umfang :

    19 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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