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62‐3: Invited Paper: Human Interface Design in Transition from Automated Driving to Manual Driving
Author(s) -
Sato Toshihisa
Publication year - 2018
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/sdtp.12278
Subject(s) - task (project management) , interface (matter) , process (computing) , computer science , transition (genetics) , control (management) , driving simulator , human–computer interaction , user interface , human–machine interface , simulation , interface design , human–machine system , engineering , artificial intelligence , systems engineering , operating system , biochemistry , chemistry , bubble , maximum bubble pressure method , gene
This paper describes a human interface design concept of automated driving systems. Control authority while using the automated systems will be back to the driver due to the operational limitation of the automated systems of Level 2 and 3. The human interface design of the automated systems in the transition process is essential for enhancing the driver's acceptance of the information provided or the automated controls. In this study, we propose the interface design of the “Request to Intervene (RtI)” that is determined based on the difference between a driver capability and a task demand (contributed by the task‐capability interface model). This concept suggests that when the driver capability exceeds the task demand before the transition mode, the transition will be successfully completed; however, the control authority cannot return to the driver smoothly and comfortably if the task demand is higher than the driver capability. In this paper, occlusion method is introduced as an estimation method of the task demand while driving. Evaluation indices for applying to a driver monitoring system is introduced, which measures the driver capability while the automated system is active. Driving simulator experiments were conducted to investigate the relationship between the driver capability and the task demand under manual drives.