Ignoring the complicated traffic condition and limited field-of-view at unsignalized intersection leave us a major challenge on preventing potential collision scenarios. This paper proposed a novel rule-based graded brake mechanism for intersection collision avoidance (ICA), using simulator-based techniques for combining the two-vehicle collision model and an automatic braking system. In particular, vehicle-to-vehicle communication was employed to ensure real-time interaction between the driving states of two vehicles, i.e., object vehicle and ego vehicle that identified as the controlled agent. Additionally, the intersection collision warning (ICW) threshold based on time to collision (TTC) was presented to warn in advance while a crash is determined. Collision scenario was constructed in PreScan simulation platform, and experimental results show the feasibility of the proposed method, and the two-stage braking strategy might accomplish stable and reliable performance for ICA.


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    Titel :

    Rule-Based Graded Braking for Unsignalized Intersection Collision Avoidance via Vehicle-to-Vehicle Communication


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Pan, Jeng-Shyang (Herausgeber:in) / Lin, Jerry Chun-Wei (Herausgeber:in) / Liang, Yongquan (Herausgeber:in) / Chu, Shu-Chuan (Herausgeber:in) / Chen, Bijun (Autor:in) / Liao, Lyuchao (Autor:in) / Zou, Fumin (Autor:in) / Zheng, Yuxin (Autor:in)

    Kongress:

    International Conference on Genetic and Evolutionary Computing ; 2019 ; Qingdao, China November 01, 2019 - November 03, 2019



    Erscheinungsdatum :

    2020-03-13


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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