In view of the unreliability of tanker rollover warning method, a highly reliable warning method for tanker rollover based on fuzzy logic is studied. Firstly, the change of rollover state is analyzed when the tanker is driving, and three rollover characterization parameters are defined. Then, the probability function of tanker rollover risk is designed, and three rollover characterization parameters are used to estimate the probability of tanker rollover, respectively. Next, the probability fusion model is established based on fuzzy logic to obtain the optimal probability of predicting the rollover occurrence. Finally, the hierarchical warning is carried out according to the optimal probability. The tanker rollover warning system is built, and real vehicle experiments are carried out respectively in the open actual road and closed test site. The experimental results show that the proposed method can accurately identify the rollover risk and conduct the effective warning. To better illustrate the warning performance, the numerical calculation shows that the proposed method can accurately quantify the rollover risk, reduce the interference of sensor error information, overcome the problems of false alarm when the tanker is driving safely and missing alarm when the tanker is in rollover risk, and improve the reliability of tanker rollover warning.


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    Title :

    Highly Reliable Warning Method for Tanker Rollover Based on Fuzzy Logic


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yadav, Sanjay (editor) / Kumar, Rahul (editor) / Zainuddin, Hidayat (editor) / Deng, Lvxiang (editor) / Pan, K. X. (author) / Wei, K. (author)

    Conference:

    International Conference on Information Control, Electrical Engineering and Rail Transit ; 2022 ; Changsha, China November 25, 2022 - November 27, 2022



    Publication date :

    2023-11-22


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English