Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving. (July 2021)

• Record Type: Journal Article
• Authors: Xing, Yang; Lv, Chen; Cao, Dongpu; Hang, Peng
• Is Part Of: Transportation research. Volume 128(2021)
• Publication Date: 2021-07
• Subjects: Automated driving vehicle -- Driver behaviors -- Cognition -- Human-autonomy collaboration -- Mutual understanding; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2021.103199
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Literature review on human behaviors and cognitive issues for collaborative automated driving vehicles. Reviews and discussion on the human situation awareness and trust for driver-vehicle collaboration. Reviews and discussion on the shared control and take over control for collaborative vehicle control modes. Reviews and discussion on human-vehicle collaboration-oriented human-machine-interface design. Abstract: The last decade witnessed a great development of automated driving vehicles (ADVs) and vehicle intelligence. The significant increment of machine intelligence poses a new challenge to the community, which is the collaboration between human drivers and vehicle autonomy. As vehicle autonomy is gaining more control authority, the roles that human drivers can play in the future need to be further clarified. In this study, literature review and perspectives on the human behaviors and cognition (HBC) for ADVs toward human-autonomy (H-A) collaboration are proposed. First, the H-A collaboration basics and key factors are reviewed. Then, the HBC issues in driver behavior modeling and understanding are discussed. Specifically, two key factors are reviewed, which are human trust and situation awareness (SA). Next, HBC in two H-A collaboration-enabled vehicle control methods, namely, shared control and take-over control, are analyzed. It is shown that the human-centered collaboration strategy that integrates driver states will largely increase the acceptance of the ADVs. Then, the HBC issues in the design of human-machine-interface (HMI) for future autonomous and collaboration-enabled ADVs are discussed. Last, challenges and future works for H-A collaboration on ADVs are analyzed to contribute to the development of understandable, trustable, and acceptable ADVs.