Since the large-scale application of fully autonomous vehicles is difficult to be commercialized in the short term, human-vehicle shared control (HVSC) is a promising technique. To implement the control authority allocation and observe the driver characteristic, it is essential to develop an efficient HVSC dynamic model with the driver’s neuromuscular characteristic (NMS). To further our previous research, a simplified HVSC dynamic model is proposed in this paper. This model simplifies the non-critical NMS parameters such as muscle spindle feedback, which has no significant feedback effect while retaining essential NMS characteristics such as stretch reflection and intrinsic properties. The model consists of a model predictive controller (MPC) coupled with a driver NMS model and a 2 DOF vehicle model. The stability is proved by Lyapunov stability theory. Moreover, a field experiment was conducted for validation of the model. The V-Box is utilized to measure the vehicle’s state signals, such as steering wheel angle and pedal stroke. Subsequently, the adaptive genetic algorithm (AGA) is employed to identify the model parameters based on the experimental results. The comparison between the experiment and the model output shows that the proposed model can accurately represent the driver’s NMS characteristics and vehicle dynamic parameters. This paper will serve as a theoretical basis for the control authority allocation for L3 class autonomous vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A simplified dynamic model with driver’s NMS characteristic for human-vehicle shared control of autonomous vehicle


    Contributors:
    Wu, Huateng (author) / Wei, Hanbing (author) / Liu, Zheng (author) / Xu, Jin (author)


    Publication date :

    2022-01-01


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Takeover Level of Autonomous Vehicle Based on Driver’s Neuromuscular Characteristic

    Hanbing, Wei / Yanhong, Wu / Yuxuan, Zhang et al. | British Library Conference Proceedings | 2020


    Takeover Level of Autonomous Vehicle Based on Driver’s Neuromuscular Characteristic

    Hanbing, Wei / Yanhong, Wu / Rui, Xu et al. | SAE Technical Papers | 2020


    Risk-based autonomous vehicle motion control with considering human driver’s behaviour

    Wei, Chongfeng / Romano, Richard / Merat, Natasha et al. | Elsevier | 2019