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Adaptive Authority Allocation of Human-Automation Shared Control for Autonomous Vehicle

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Abstract

Great advances had been achieved in the discipline of environmental perception, motion planning and control strategy implementation, however, fully autonomous vehicle is still far from large-scale commercial application. The concept of “human-automation shared control” provides a promising solution to enhance autonomous driving safety, to which great research effort has been contributed in recent years. Nevertheless, more attention should be given to the following aspects. The present shared control strategy either only considers the discontinuous switching control between driver and ADS or investigates the simple effect of driver’s behavior in specific scenarios. The adaptive authority allocation between the driver’s active assistance and ADS hasn’t been investigated yet. In this paper, a shared control experiment with driver’s active assistance is conducted in scheduled traffic scenarios to observe the state of vehicle and arm’ EMG signal. After that, we construct a feature classification algorithm for shared control authority by clustering the experimental data. Then, a SCS with incremental PID controller and 2 DOF vehicle dynamic model is proposed. For validation of the SCS, the comparison of vehicle performance for different control authority illustrates that SCS can allocate appropriate control authority to improve the safety.

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Abbreviations

AV:

autonomous vehicle

ADS:

autonomous driving system

NMS:

neuromuscular system

SCS:

share control system

HIL:

hardware-in-loop

PCA:

principal component analysis

RLS:

recursive least squares

EMG:

electromyography

DOF:

degree-of-freedom

ARV:

average rectified value

HIL:

hardware-in-loop

ADAS:

advanced driver-assistance systems

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Acknowledgement

This work was supported by the National Key Research and Development Program of China (2018YFB1600500), National Natural Science Foundation of China (Grant No. 51305472, 51705051), Natural Science Foundation Project of the Chongqing Municipal Science and Technology Commission (Grant No. KJQN201800714). The authors would also like to thank the reviewers for their corrections and helpful suggestions.

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Correspondence to Hanbing Wei.

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Wu, Y., Wei, H., Chen, X. et al. Adaptive Authority Allocation of Human-Automation Shared Control for Autonomous Vehicle. Int.J Automot. Technol. 21, 541–553 (2020). https://doi.org/10.1007/s12239-020-0051-6

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