scholarly journals The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 42
Author(s):  
Lichao Yang ◽  
Mahdi Babayi Semiromi ◽  
Yang Xing ◽  
Chen Lv ◽  
James Brighton ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Haptic Feedback ◽  
Hand Movement ◽  
Transition Process ◽  
Recognition System ◽  
Steering Wheel ◽  
Automated Driving ◽  
Driver Behaviour ◽  
Active Mode ◽  
The Impact

In conditionally automated driving, the engagement of non-driving activities (NDAs) can be regarded as the main factor that affects the driver’s take-over performance, the investigation of which is of great importance to the design of an intelligent human–machine interface for a safe and smooth control transition. This paper introduces a 3D convolutional neural network-based system to recognize six types of driver behaviour (four types of NDAs and two types of driving activities) through two video feeds based on head and hand movement. Based on the interaction of driver and object, the selected NDAs are divided into active mode and passive mode. The proposed recognition system achieves 85.87% accuracy for the classification of six activities. The impact of NDAs on the perspective of the driver’s situation awareness and take-over quality in terms of both activity type and interaction mode is further investigated. The results show that at a similar level of achieved maximum lateral error, the engagement of NDAs demands more time for drivers to accomplish the control transition, especially for the active mode NDAs engagement, which is more mentally demanding and reduces drivers’ sensitiveness to the driving situation change. Moreover, the haptic feedback torque from the steering wheel could help to reduce the time of the transition process, which can be regarded as a productive assistance system for the take-over process.

scholarly journals Optimal Time Intervals in Two-Stage Takeover Warning Systems With Insight Into the Drivers’ Neuroticism Personality

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei Zhang ◽  
Yilin Zeng ◽  
Zhen Yang ◽  
Chunyan Kang ◽  
Changxu Wu ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Proper Time ◽  
Steering Wheel ◽  
Optimal Time ◽  
Time Interval ◽  
Warning Systems ◽  
Automated Driving ◽  
Time Intervals ◽  
Two Stage ◽  
Hands On

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.

Function-Specific Uncertainty Communication in Automated Driving

2019 ◽  
Vol 11 (2) ◽  
pp. 75-97
Author(s):  
Alexander Kunze ◽  
Stephen J. Summerskill ◽  
Russell Marshall ◽  
Ashleigh J. Filtness
Keyword(s):  
Augmented Reality ◽  
Situation Awareness ◽  
Driving Simulator ◽  
Automated Driving ◽  
Driving Experience ◽  
Visual Variables ◽  
Simulator Study ◽  
The Impact

Conveying the overall uncertainties of automated driving systems was shown to improve trust calibration and situation awareness, resulting in safer takeovers. However, the impact of presenting the uncertainties of multiple system functions has yet to be investigated. Further, existing research lacks recommendations for visualizing uncertainties in a driving context. The first study outlined in this publication investigated the implications of conveying function-specific uncertainties. The results of the driving simulator study indicate that the effects on takeover performance depends on driving experience, with less experienced drivers benefitting most. Interview responses revealed that workload increments are a major inhibitor of these benefits. Based on these findings, the second study explored the suitability of 11 visual variables for an augmented reality-based uncertainty display. The results show that particularly hue and animation-based variables are appropriate for conveying uncertainty changes. The findings inform the design of all displays that show content varying in urgency.

Function-Specific Uncertainty Communication in Automated Driving

2022 ◽  
pp. 1002-1026
Author(s):  
Alexander Kunze ◽  
Stephen J. Summerskill ◽  
Russell Marshall ◽  
Ashleigh J. Filtness
Keyword(s):  
Augmented Reality ◽  
Situation Awareness ◽  
Driving Simulator ◽  
Automated Driving ◽  
Driving Experience ◽  
Visual Variables ◽  
Simulator Study ◽  
The Impact

Conveying the overall uncertainties of automated driving systems was shown to improve trust calibration and situation awareness, resulting in safer takeovers. However, the impact of presenting the uncertainties of multiple system functions has yet to be investigated. Further, existing research lacks recommendations for visualizing uncertainties in a driving context. The first study outlined in this publication investigated the implications of conveying function-specific uncertainties. The results of the driving simulator study indicate that the effects on takeover performance depends on driving experience, with less experienced drivers benefitting most. Interview responses revealed that workload increments are a major inhibitor of these benefits. Based on these findings, the second study explored the suitability of 11 visual variables for an augmented reality-based uncertainty display. The results show that particularly hue and animation-based variables are appropriate for conveying uncertainty changes. The findings inform the design of all displays that show content varying in urgency.

Is it Good or Bad to Provide Driver Fatigue Warning During Take-Over in Highly Automated Driving?

2021 ◽  
pp. 036119812110469
Author(s):  
Jianwei Niu ◽  
Chuang Ma
Keyword(s):  
Situation Awareness ◽  
Steering Wheel ◽  
Automated Driving ◽  
The Road ◽  
Hands On ◽  
Level 3 ◽  
Processing Techniques ◽  
Fatigue Detection ◽  
Different Levels ◽  
Tor Tor

When and how the driver should be intervened to relieve the fatigue status in Society of Automotive Engineers Level 3 automated driving has raised numerous debates. In this paper, we identify the driver’s fatigue level according to the driver’s facial features before the system issues the take-over request (TOR), and then perform the fatigue warning (FW) intervention to investigate whether the driver would be better prepared for taking over the vehicle safely and efficiently. In a simulator-based study, we compared the driver’s driving performance under the condition of whether a FW intervention was provided before a possible TOR, with the aim to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving. A FW + TOR condition was compared with a TOR-only condition using a within-subject design with 30 participants. Under the effect of FW, participants exhibited better take-over performance; for example, they gazed at the road and placed their hands on the steering wheel earlier before taking over the vehicle. Moreover, in the FW + TOR state, they also exhibited better take-over performance, with a shorter average braking reaction time and a higher average speed, which reflects that the driver’s speed is more stable during the take-over of the vehicle and that the take-over task can be completed with a smaller deceleration. Furthermore, it is concluded that the FW (5 s before TOR) + TOR mode has greater potential to increase the safety and acceptance of automated driving, and could reduce the driver’s safety risk in a fatigue state when driving automatically compared with the FW (10 s before TOR) + TOR mode. It is concluded that FW (5 s before TOR) + TOR mode has the potential to increase safety and acceptance of automated driving as compared with systems that provide only TORs. In addition, we need to design take-over scenarios and non-driving-related tasks with different levels of complexity to satisfy subsequent research. The fatigue detection method based on image-processing techniques also needs further improvement.

scholarly journals Effects of User Interfaces on Take-Over Performance: A Review of the Empirical Evidence

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 162
Author(s):  
Soyeon Kim ◽  
René van Egmond ◽  
Riender Happee
Keyword(s):  
User Interface ◽  
Situation Awareness ◽  
User Interfaces ◽  
Situational Awareness ◽  
Selection Criterion ◽  
Auditory Modality ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Positive Effects ◽  
High Urgency

In automated driving, the user interface plays an essential role in guiding transitions between automated and manual driving. This literature review identified 25 studies that explicitly studied the effectiveness of user interfaces in automated driving. Our main selection criterion was how the user interface (UI) affected take-over performance in higher automation levels allowing drivers to take their eyes off the road (SAE3 and SAE4). We categorized user interface (UI) factors from an automated vehicle-related information perspective. Short take-over times are consistently associated with take-over requests (TORs) initiated by the auditory modality with high urgency levels. On the other hand, take-over requests directly displayed on non-driving-related task devices and augmented reality do not affect take-over time. Additional explanations of take-over situation, surrounding and vehicle information while driving, and take-over guiding information were found to improve situational awareness. Hence, we conclude that advanced user interfaces can enhance the safety and acceptance of automated driving. Most studies showed positive effects of advanced UI, but a number of studies showed no significant benefits, and a few studies showed negative effects of advanced UI, which may be associated with information overload. The occurrence of positive and negative results of similar UI concepts in different studies highlights the need for systematic UI testing across driving conditions and driver characteristics. Our findings propose future UI studies of automated vehicle focusing on trust calibration and enhancing situation awareness in various scenarios.

Delays in Manual Reaching Are Associated with Impaired Functional Abilities in Early Dementia Patients

2015 ◽  
Vol 40 (1-2) ◽  
pp. 63-71 ◽  
Author(s):  
Casper de Boer ◽  
Johan J.M. Pel ◽  
Johannes van der Steen ◽  
Francesco Mattace-Raso
Keyword(s):  
Daily Living ◽  
Hand Movement ◽  
Hand Tracking ◽  
Functional Abilities ◽  
Dementia Patients ◽  
Early Dementia ◽  
Tracking Devices ◽  
The Impact ◽  
Hand Response

Background/Aims: Recent evidence shows that early dementia patients have deficits in manual reaching tasks. It is important to understand the impact of these functional disabilities on their quality of life. The aim of this study was to investigate if there is an association between manual reaching and measures of (instrumental) activities of daily living (IADL) in a group of patients with cognitive complaints. Methods: The manual reaching performance of 27 patients was assessed in detail with eye and hand tracking devices. Patients were divided into three groups based on self-reported loss of IADL function. Parameters describing hand response and movement times were compared between groups. Results: Patients with loss of IADL function in ≥1 domain had delayed hand response and hand movement times towards visible targets compared to patients with no loss of IADL function. Conclusion: Delays in manual reaching movements are related to the degree of loss of IADL function in early dementia patients.

Assessing the Effect of Countdown Featured TOR Signal on Drivers in Automated Driving Mode Change

2020 ◽  
Vol 64 (1) ◽  
pp. 1213-1217
Author(s):  
HyunJoo Park ◽  
HyunJae Park ◽  
Sang-Hwan Kim
Keyword(s):  
Reaction Time ◽  
Situation Awareness ◽  
Time Preference ◽  
Automated Driving ◽  
Mode Change ◽  
Driving Mode

In conditional automated driving, drivers may be required starting manual driving from automated driving mode after take-over request (TOR). The objective of the study was to investigate different TOR features for drivers to engage in manual driving effectively in terms of reaction time, preference, and situation awareness (SA). Five TOR features, including four features using countdown, were designed and evaluated, consisted of combinations of different modalities and codes. Results revealed the use of non-verbal sound cue (beep) yielded shorter reaction time while participants preferred verbal sound cue (speech). Drivers' SA was not different for TOR features, but the level of SA was affected by different aspects of SA. The results may provide insights into designing multimodal TOR along with drivers' behavior during take-over tasks.

scholarly journals Restraining Surface Charge Accumulation and Enhancing Surface Flashover Voltage through Dielectric Coating

Coatings ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 750
Author(s):  
Jixing Sun ◽  
Sibo Song ◽  
Xiyu Li ◽  
Yunlong Lv ◽  
Jiayi Ren ◽  
...  
Keyword(s):  
Charge Transfer ◽  
Electric Field ◽  
Electric Fields ◽  
Transition Process ◽  
Metallic Particle ◽  
Particle Charging ◽  
Insulating Surfaces ◽  
Surface Flashover ◽  
Charging Time ◽  
The Impact

A conductive metallic particle in a gas-insulated metal-enclosed system can charge through conduction or induction and move between electrodes or on insulating surfaces, which may lead to breakdown and flashover. The charge on the metallic particle and the charging time vary depending on the spatial electric field intensity, the particle shape, and the electrode surface coating. The charged metallic particle can move between the electrodes under the influence of the spatial electric field, and it can discharge and become electrically conductive when colliding with the electrodes, thus changing its charge. This process and its factors are mainly affected by the coating condition of the colliding electrode. In addition, the interface characteristics affect the particle when it is near the insulator. The charge transition process also changes due to the electric field strength and the particle charging state. This paper explores the impact of the coating material on particle charging characteristics, movement, and discharge. Particle charging, movement, and charge transfer in DC, AC, and superimposed electric fields are summarized. Furthermore, the effects of conductive particles on discharge characteristics are compared between coated and bare electrodes. The reviewed studies demonstrate that the coating can effectively reduce particle charge and thus the probability of discharge. The presented research results can provide theoretical support and data for studying charge transfer theory and design optimization in a gas-insulated system.

scholarly journals Multimodal Mixed Reality Impact on a Hand Guiding Task with a Holographic Cobot

2020 ◽  
Vol 4 (4) ◽  
pp. 78
Author(s):  
Andoni Rivera Pinto ◽  
Johan Kildal ◽  
Elena Lazkano
Keyword(s):  
Augmented Reality ◽  
Industrial Production ◽  
User Study ◽  
Haptic Feedback ◽  
Mixed Reality ◽  
Robot Arm ◽  
Pick And Place ◽  
Place Task ◽  
Guidance Technique ◽  
The Impact

In the context of industrial production, a worker that wants to program a robot using the hand-guidance technique needs that the robot is available to be programmed and not in operation. This means that production with that robot is stopped during that time. A way around this constraint is to perform the same manual guidance steps on a holographic representation of the digital twin of the robot, using augmented reality technologies. However, this presents the limitation of a lack of tangibility of the visual holograms that the user tries to grab. We present an interface in which some of the tangibility is provided through ultrasound-based mid-air haptics actuation. We report a user study that evaluates the impact that the presence of such haptic feedback may have on a pick-and-place task of the wrist of a holographic robot arm which we found to be beneficial.

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