The Autonomous emergency braking system (AEB) has been widely equipped in the design and manufacture of vehicles as an active safety system for preventing rear-end collisions. It has shown great safety potential in preventing collisions and reducing collision injuries. However, there are differences in the response characteristics of drivers in emergency scenarios due to individual differences and driving habits. The impact of different driver types on the safety performance of AEB systems has not been evaluated. In this study, the typical driver response model was constructed by selecting driver response features representing alertness and braking. The AEB algorithm of distance and situation awareness was combined with the kinematic of vehicle before the collision to construct a simulation case based on the rear-end collisions in the China in-depth accident study database (CIDAS). The collision avoidance percentage, the impact speed, and the minimum relative distance were used as evaluation indicators to evaluate the AEB system safety performance for different driver types. The results show that the AEB system could avoid more than 85% of rear-end collisions. The collision speed could be reduced if the collision cannot be avoided. Slower reaction times negatively impact the safety benefits of AEB systems. The larger braking deceleration has a positive effect on the safety benefit of the AEB system. The safety benefit of the Berkeley algorithm is greatly affected by the driver’s response features compared with a situation and threat assessment algorithm (SATAA). Therefore, it is beneficial to improve the safety benefit of the AEB system to adjust the AEB system parameters according to the response features of drivers.


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    Title :

    The Effect of Driver’s Response Features on Safety Effectiveness of Autonomous Emergency Braking


    Additional title:

    Sae Technical Papers


    Contributors:
    Liu, Haoxue (author) / Kang, Kai (author) / Wei, Tianzheng (author) / Zhu, Tong (author)

    Conference:

    SAE 2022 International Automotive Safety, Security and Testing Congress ; 2022



    Publication date :

    2022-12-16




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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