In conditional automated driving (SAE Level 3), drivers are required to take over their vehicles when the automated systems fail. Non-driving related tasks (NDRTs) can positively or negatively affe...

Conditional automated driving [level 3, Society of Automotive Engineers (SAE)] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism (high vs. low). Each driver experienced takeover under the two-stage warning systems with four time intervals (i.e., 3, 5, 7, and 9 s). The takeover performance (i.e., hands-on-steering-wheel time, takeover time, and maximum resulting acceleration) and subjective opinions (i.e., appropriateness and usefulness) for time intervals and situation awareness (SA) were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation (fast hands-on steering wheel responses and sufficient SA). Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers.

Research on the acquisition of spatial knowledge not only enriches our understanding of the theory of spatial knowledge representation but also creates practical value for the application of spatial knowledge. The aim of this study is to understand the impact of different learning methods on the acquisition of spatial knowledge, including the role of 2D maps, the difference between physical interaction and virtual interaction, and whether passive learning can replace active learning in virtual environments. One experiment was conducted, in which landmark knowledge and configurational knowledge were measured. Results indicate that 2D maps play a supporting role in acquiring both landmark knowledge and configurational knowledge. In addition, physical learning was associated with better spatial knowledge representation compared with virtual learning. An analysis of observational data in the third comparison found no significant difference between passive learning and active learning using virtual street view maps. However, with high-quality learning materials, passive learning can contribute to the acquisition of spatial knowledge more efficiently than active learning.

Egocentric distance perception refers to the perception of distance from a target to a perceiver, which is an important component of visual space perception. It is important to activities in virtual environments and influenced by several factors, such as action capacities and visual cues. However, few studies have investigated such aspects. Hence, Experiments 1 and 2 investigated the effect of using experience and visual cues, respectively, of virtual arms on egocentric distance perception in near and far spaces at equal, prolonged, and shortened lengths of a virtual arm. Results revealed that using experience and visual cues of the virtual arm had a significant effect on egocentric distance perception when the length of virtual arm was equal to the real arm and prolonged but not when shortened. The egocentric distance perception on the conditions of having using experience and virtual arm was most precise. The findings provide implications for the design and implementation of virtual body self-representation in virtual environments.

Informative warnings can improve takeover performance in automated vehicles, but improper or excessive information may hinder it. This study investigates the optimal amount of information in urgent and non-urgent autonomous takeover transitions. Forty-five drivers were randomly assigned to groups receiving different amounts of the selected takeover warning information elements. Each group completed simulated takeover tasks in four scenarios with different urgency. Takeover performance, situation awareness, and stress levels were measured. The results indicate that, in urgent situations, single-element assistance delays takeover response, while three elements increase failure risk. However, dual-element assistance yields faster response, equivalent awareness, and minimal stress. In non-urgent situations, having three elements leads to the best awareness and lowest stress compared with having fewer elements. In conclusion, an appropriate and non-overwhelming level of information facilitates urgent takeover performance, whereas greater information is advantageous in non-urgent cases. These findings provide insights into designing appropriate warning amount assistants for automated driving takeover requests across varying time-pressure situations.