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

TL;DR

This paper reviews decision-making processes in driver-automation shared control systems, emphasizing human modeling, interaction strategies, and future challenges to improve human-vehicle cooperation.

Contribution

It provides a comprehensive survey of architectures, human driver modeling, and interaction strategies in shared control systems, highlighting future research directions.

Findings

Analysis of human driver modeling approaches

Overview of interaction strategies in shared control

Discussion of future challenges and opportunities

Abstract

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.