An analysis of physiological responses as indicators of driver takeover readiness in conditionally automated driving.

By the year 2045, it is projected that Autonomous Vehicles (AVs) will make up half of the new vehicle market. Successful adoption of AVs can reduce drivers' stress and fatigue, curb traffic congestion, and improve safety, mobility, and economic efficiency. Due to the limited intelligence in relevant technologies, human-in-the-loop modalities are still necessary to ensure the safety of AVs at current or near future stages, because the vehicles may not be able to handle all emergencies. Therefore, it is important to know the takeover readiness of the drivers to ensure the takeover quality and avoid any potential accidents. To achieve this, a comprehensive understanding of the drivers' physiological states is crucial. However, there is a lack of systematic analysis of the correlation between different human physiological responses and takeover behaviors which could serve as important references for future studies to determine the types of data to use. This paper provides a comprehensive analysis of the effects of takeover behaviors on the common physiological indicators. A program for conditional automation was developed based on a game engine and applied to a driving simulator. The experiment incorporated three types of secondary tasks, three takeover events, and two traffic densities. Brain signals, Skin Conductance Level (SCL), and Heart Rate (HR) of the participants were collected while they were performing the driving simulations. The Frontal Asymmetry Index (FAI) (as an indicator of engagement) and Mental Workload (MWL) were calculated from the brain signals to indicate the mental states of the participants. The results revealed that the FAI of the drivers would slightly decrease after the takeover alerts were issued when they were doing secondary tasks prior to the takeover activities, and the higher difficulty of the secondary tasks could lead to lower overall FAI during the takeover periods. In contrast, The MWL and SCL increased during the takeover periods. The HR also increased rapidly at the beginning of the takeover period but dropped back to a normal level quickly. It was found that a fake takeover alert would lead to lower overall HR, slower increase, and lower peak of SCL during the takeover periods. Moreover, the higher traffic density scenarios were associated with higher MWL, and a more difficult secondary task would lead to higher MWL and HR during the takeover activities. A preliminary discussion of the correlation between the physiological data, takeover scenario, and vehicle data (that relevant to takeover readiness) was then conducted, revealing that although takeover event, SCL, and HR had slightly higher correlations with the maximum acceleration and reaction time, none of them dominated the takeover readiness. In addition, the analysis of the data across different participants was conducted, which emphasized the importance of considering standardization or normalization of the data when they were further used as input features for estimating takeover readiness. Overall, the results presented in this paper offer profound insights into the patterns of physiological data changes during takeover periods. These findings can be used as benchmarks for utilizing these variables as indicators of takeover preparedness and performance in future research endeavors.

Shared autonomy in assistive mobile robots: a review.

PURPOSE: Shared autonomy has played a major role in assistive mobile robotics as it has the potential to effectively balance user satisfaction and smooth functioning of systems by adapting itself to each user's needs and preferences. Many shared control paradigms have been developed over the years. However, despite these advancements, shared control paradigms have not been widely adopted as there are several integral aspects that have not fully matured. The purpose of this paper is to discuss and review various aspects of shared control and the technologies leading up to the current advancements in shared control for assistive mobile robots. METHODS: A comprehensive review of the literature was conducted following a dichotomy of studies from the pre-2000 and the post-2000 periods to focus on both the early developments and the current state of the art in this domain. RESULTS: A systematic review of 135 research papers and 7 review papers selected from the literature was conducted. To facilitate the organization of the reviewed work, a 6-level ladder categorization was developed based on the extent of autonomy shared between the human and the robot in the use of assistive mobile robots. This taxonomy highlights the chronological improvements in this domain. CONCLUSION: It was found that most prior studies have focussed on basic functionalities, thus paving the way for research to now focus on the higher levels of the ladder taxonomy. It was concluded that further research in the domain must focus on ensuring safety in mobility and adaptability to varying environments.Implications for rehabilitationShared autonomy in assistive mobile robots plays a vital role in effectively adapting to ensure safety while also considering the user comfort.User's immediate desires should be considered in decision making to ensure that the users are in control of the assistive robots.The current focus of research should be towards successful adaptation of the assistive mobile robots to varying environments to assure safety of the user.