A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 7 Issue 5
Sep.  2020

IEEE/CAA Journal of Automatica Sinica

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Wenshuo Wang, Xiaoxiang Na, Dongpu Cao, Jianwei Gong, Junqiang Xi, Yang Xing and Fei-Yue Wang, "Decision-Making in Driver-Automation Shared Control: A Review and Perspectives," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1289-1307, Sept. 2020. doi: 10.1109/JAS.2020.1003294
Citation: Wenshuo Wang, Xiaoxiang Na, Dongpu Cao, Jianwei Gong, Junqiang Xi, Yang Xing and Fei-Yue Wang, "Decision-Making in Driver-Automation Shared Control: A Review and Perspectives," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1289-1307, Sept. 2020. doi: 10.1109/JAS.2020.1003294

Decision-Making in Driver-Automation Shared Control: A Review and Perspectives

doi: 10.1109/JAS.2020.1003294
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  • Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control. The human driver, as an essential agent in the driver-vehicle shared control systems, should be precisely modeled regarding their cognitive processes, control strategies, and decision-making processes. The interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of humans. Many open-ended questions arise, such as what proper role of human drivers should act in a shared control scheme? How to make an intelligent decision capable of balancing the benefits of agents in shared control systems? Due to the advent of these attentions and questions, it is desirable to present a survey on the decision making between human drivers and highly automated vehicles, to understand their architectures, human driver modeling, and interaction strategies under the driver-vehicle shared schemes. Finally, we give a further discussion on the key future challenges and opportunities. They are likely to shape new potential research directions.

     

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  • 1An automated driving agent refers to as a well-designed automatic controller in automated vehicle systems.
    2 Automation is a technology that actively selects data, transforms informa-tion, makes decisions, or controls processes [11].
    3 The definition of shared control is slightly different over different research fields because there is no single definition for shared control that is used across application domains. More detailed descriptions are referred to see Section II in review paper [21].
    4 The task-level shared control refers to as a shared-control system that allows human drivers to decompose a whole driving task into subtasks and allocate some of them to the automated driving agent (namely, share at the task level [44] rather than the servo level), which is slightly different from the traded control [5], [20], [21].
    5 The “loop” can refer to an information processing control loop (i.e., attentive to driving task) or a sensory-motor control loop (i.e., vehicle control), or both [63]. Here, the “loop” refers to as a sensory-motor control loop.
    6 Compatibility here is referred to as the quality describing the fit or match [32] between a human driver and automated driving agents, regarding the outer (e.g., interfaces) and inner (e.g., cognition) interactions [137] between them.
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    • Providing a review of decision-making in driver-automation shared control.
    • Discussing human driver models from different perspectives.
    • Providing future challenges and opportunities in driver-automation shared control systems.

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