Lower Mental Workload Research Articles

Measuring the effect of mental workload and explanations on appropriate AI reliance using EEG

ABSTRACT AI is anticipated to improve human decision-making across various domains, often in high-stakes, difficult tasks. However, human reliance on AI recommendations is often inappropriate. A common approach to address this is to provide explanations about the AI output to decision makers, but results have been mixed so far. It often remains unclear when people can rely appropriately on AI and when explanations can help. In this work, we conducted a lab experiment (N = 34) to investigate how the appropriateness of human reliance on (explainable) AI depends on the mental workload induced by different decision difficulties. Instead of self-assessments, we used EEG (Emotiv Epoc Flex head cap, 32 wet electrodes) to more directly measure participants' mental workload. We found that the difficulty of a decision, indicated by the induced mental workload, strongly influences participants' ability to rely appropriately on AI, as assessed through relative self-reliance, relative AI reliance, and decision accuracy with and without AI. While reliance was appropriate for low mental workload decisions, participants were prone to overreliance in high mental workload decisions. Explanations had no significant effect in either case. Our results imply that alternatives to the common ‘recommend-and-explain’ approach should be explored to assist human decision-making in challenging tasks.

Determining the effect of environmental factors, work postures and mental workload on musculoskeletal disorders in rescue workers and accidents of one of the water and sewage companies in Iran.

Musculoskeletal disorders are one of the most important problems faced by ergonomists today. This study was conducted with the aim of investigating the effect of weather conditions, working conditions and mental workload on musculoskeletal disorders of rescuers and water and sewage company accidents in hot and cold seasons. The present study was a longitudinal study that was performed on all employees of rescue and disaster teams of Shiraz Water and Sewerage Company in Iran (184 people) by census. Demographic and Nordic questionnaires, NASA Load Index (NASA-TLX), work environment assessment with temperature screening checklist and workplace ergonomic risk factor (WERA) assessment method were performed by the researcher. The collected data were analyzed using SPSS version 23 software and parametric and non-parametric statistical tests. The results showed that the highest and lowest prevalence of musculoskeletal disorders related to knee and back in winter and thigh in summer with prevalence of 57.1, 55.4 and 6%. The comparison of exposure to heat stress factors in summer and winter seasons showed that the temperature factors and work clothes of the workers in both seasons are in worse conditions than other factors (P < 0968). The results of the mental workload of people in two seasons showed that the highest and lowest mental workload is related to physical changes in the winter season and frustration in the summer season, and this relationship was significant (P < 0.001). Using multiple logistic regression model, the potential risk factors for musculoskeletal injuries including age, height, BMI, level of education and work experience in both hot and cold seasons were compared. The results showed that in summer, work experience (OR = 1.16 (1.06-1.28.)) and height (OR = 1.03(0.98-1.08) had a direct effect on the prevalence of pain and discomfort arranged in the back areas. One year of increase in work experience significantly increases the chance of a disorder in the back by 16% and a one centimeter increase in height increases the chance of a disorder in the lumbar region by 3%, although this relationship is significant. It is recommended that suitable solutions such as using appropriate and up-to-date mechanical tools, reducing activity time, increasing rest time, increasing the number of personnel in order to reduce mental workload, using work clothes suitable for the season and type of work, and ergonomics training for workers are on the agenda of company officials. Water and sewage should be placed.

Classification of gait variation under mental workload in big five personalities

BackgroundHuman behavior patterns involve mutual interactions among psychology, physiology, and stress, which are all associated with gait at different grades. Research questionsThe study aims to reveal the interrelationship among personality, mental workload, and gait patterns by capturing gait variations using inertial sensors. It also assesses individual personality traits and simulates stress to construct a gait classification model. MethodsSixty participants were instructed to perform regular, low, and high mental workload walking on the corridor to simulate a natural setting walking. Meanwhile inertial measurement units (IMUs) were placed on eight body parts. Mental workload was induced using the auditory n-back task, and their Big Five personality traits were evaluated. Gait data from IMUs were categorized into nine classifications of average, low, and high Big Five Inventory scores with three levels of mental workload walking. Subsequently, the segmentation gait data were used as input features for classifications in deep learning models, employing a sliding window long short-term memory network for nine classifications for different personality dimensions. ResultsThe results indicated average accuracies of nine classifications were 83.6 % for Openness, 84.4 % for Conscientiousness, 82.0 % for Extraversion, 85.2 % for Agreeableness, and 84.5 % for Neuroticism across all IMU placements. Remarkably, gait data from the lower back IMU achieved the highest model performance, with an average accuracy of 92.7 %, in classifying the different levels of personality and mental workload walking. In contrast, the left wrist and chest showed several misclassifications among regular, low, and high mental workload walking across personality traits. SignificanceSuccessful classification can help monitor an individual's mental state in real time and analyze personality dimensions, providing feedback and suggestions. The present study demonstrated that gait characteristics can contribute to more profound and personalized health information.

Paramedic Mental Workload in Pandemic Covid-19 Era

The number of Covid-19 patients hospitalized continues to increase in line with the increase in Covid-19 cases in Indonesia. The increasing number of Covid-19 patients in hospitals is increasing the workload of paramedics. High workloads will cause saturation and fatigue. In addition, an increase in the number of Covid-19 patients increases anxiety and depression will be infected when treating patients. Paramedics should also use personal protective equipment during shift guards which causes dehydration and discomfort. This situation can degrade the quality of service to patients. The study aims to measure the mental workload of paramedics by NASA-TLX (National Aeronautics and Space Administration Task Load Index) method and find out the factors that affect mental workload levels. This research is a quantitative research with a cross sectional approach. The research was conducted at Hospital X type C in Malang Regency in October 2020. The samples used were all 100 Hospital X paramedics. Research instruments in the form of questionnaires shared through Google Form. Data analysis is done with descriptive analysis and Chi-Square analysis with p value &lt;0.05. The results found paramedics had a low mental workload of 1%, a moderate mental load of 3%, a high mental workload of 47%, and a very high mental workload of 49%. The Chi-Square test results found that age factors had an effect on the mental workload level of paramedics.

Automated assessment of mental workload from PPG sensor data using cross-wavelet coherence and transfer learning.

Highly complex cognitive works require more brain power. The productivity of a person suffers due to this strain, which is sometimes referred to as a mental burden or psychological load. A person's mental health and safety in high-stress working conditions can be improved with the help of mental workload assessment. A photoplethysmogram (PPG) signal is a non-invasive and easily acquired physiological signal that contains information related to blood volume changes in the micro-vascular bed of tissues and can indicate psychologically relevant information to assess a person's mental workload (MW). An individual under a high MW possesses an increase in sympathetic nervous system activity, which results in morphological changes in the PPG waveform. In this work, a time-frequency analysis framework is developed to capture these distinguishing PPG features for the automatic assessment of MW. In particular, a cross-wavelet coherence (WTC) approach is proposed to extract simultaneous time-frequency information of the PPG during MW relative to the resting PPG. The suggested technique is validated on a publicly available data set of 22 healthy individuals who took part in an N-back task with PPG recording. Under three different fixed window lengths, images are obtained using WTC between PPG records during N-back task activity and rest. The images are used further to obtain PPG classification in two broad classes of low and high MW using a customized pre-trained Inception-V3 model. The best validation and test accuracy of 93.86% and 93.07%, respectively obtained in the window setting of 1200 samples used for WTC image creation.

Common Subjective Mental Workload Assessment Measures: Advantages and Disadvantages

Background: The amount of mental resources required to perform simultaneously a series tasks is considered as mental workload (MWL). High and Low mental workload in the workplace is usually associated with mental fatigue, decreased performance, human error, and even harmful long-term health effects. Among the various MWL assessment techniques, the outcome measures such as questionnaires are easier and more practical in workplace settings. We aimed to compare the three current commonly advocated and used questionnaires. Material and Methods: Three common different outcome measures for evaluation of the MWL are NASA Task Load Index (NASA-TLX), Subjective Workload Assessment Technique (SWAT), and the CarMen-Q workload questionnaire. Among them the NASA-TLX is well known and more popular with six subscales that are used extensively in industrial and official workplaces. SWAT is the simplest one with three dimensions. The NASA-TLX is preferable method because of its higher sensitivity, especially in low MWL conditions. The CarMen-Q questionnaire is a new questionnaire with 29 items and 4 subscales that focuses on cognitive workload and mental fatigue. Conclusion: SWAT is the simplest and less sensitive measure than the NASA-TLX and CarMen-Q questionnaires. In contrast, the NASA-TLX is widely used and more known instrument for MWL evaluation.

Acute effects of (-)-gallocatechin gallate-rich green tea extract on the cerebral hemodynamic response of the prefrontal cortex in healthy humans.

The benefits of long-term consumption of green tea on the brain are well known. However, among many ingredients of green tea, the acute effects of (-)-gallocatechin gallate-rich green tea extract (GCG-GTE), have received comparatively less attention. Herein, we investigated the acute effects of oral ingestion of green tea with GCG-GTE, which contains close replicas of the ingredients of hot green tea, on task-dependent hemodynamics in the prefrontal cortex of healthy adult human brains. In this randomized, double-blind, placebo-controlled, parallel group trial, 35 healthy adults completed computerized cognitive tasks that demand activation of the prefrontal cortex at baseline and 1 h after consumption of placebo and 900 mg of GCG-GTE extract supplement. During cognitive testing, hemodynamic responses (change in HbO2 concentration) in the prefrontal cortex were assessed using functional near-infrared spectroscopy (fNIRS). In fNIRS data, significant group x session interactions were found in the left (p = 0.035) and right (p = 0.036) dorsolateral prefrontal cortex (DLPFC). In behavioral data, despite the numerical increase in the GCG-GTE group and the numerical decrease in the Placebo group, no significant differences were observed in the cognitive performance measure between the groups. The result suggests a single dose of orally administered GCG-GTE can reduce DLPFC activation in healthy humans even with increased task demand. GCG-GTE is a promising functional material that can affect neural efficiency to lower mental workload during cognitively demanding tasks. However, further studies are needed to verify this.

Neck Muscle Coactivation Response to Varied Levels of Mental Workload During Simulated Flight Tasks.

To evaluate neck muscle coactivation across different levels of mental workload during simulated flight tasks. Neck pain (NP) is highly prevalent among military aviators. Given the complex nature within the flight environment, mental workload may be a risk factor for NP. This may induce higher levels of neck muscle coactivity, which over time may accelerate fatigue, increase neck discomfort, and affect flight task performance. Three counterbalanced mental workload conditions represented by simulated flight tasks modulated by interstimulus frequency and complexity were investigated using the Modifiable Multitasking Environment (ModME). The primary measure was a neck coactivation index to describe the neuromuscular effort of the neck muscles as a system. Additional measures included perceived workload (NASA TLX), subjective discomfort, and task performance. Participants (n = 60; 30M, 30F) performed three test conditions over 1hr each while seated in a simulated seating environment. Neck coactivation indices (CoA) and subjective neck discomfort corresponded with increasing level of mental workload. Average CoAs for low, medium, and high workloads were: .0278(SD = .0232), .0286(SD = .0231), and .0295(SD = .0228), respectively. NASA TLX mental, temporal, effort, and overall scores also increased with the level of mental workload assigned. For ModME task performance, the overall performance score, monitoring accuracy, and resource management accuracy decreased while reaction times increased with the increasing level of mental workload. Communication accuracy was lowest with the low mental workload but had higher reaction times relative to increasing workload. Mental workload affects neck muscle coactivation during combinations of simulated flight tasks within a simulated helicopter seating environment. The results of this study provide insights into the physical response to mental workload. With increasing multisensory modalities within the work environment, these insights may assist the consideration of physical effects from cognitive factors.

53 Working Memory Network Load Engagement in Schizophrenia

Objective:Cognitive deficits in patients diagnosed with schizophrenia are a core feature of the disorder. There are currently no treatments for these cognitive deficits. Our aim was to examine and compare patterns of increased versus decreased activity in the central executive network (CEN), salience network (SN), and default mode network (DMN) between healthy controls (HCs) and patients diagnosed with schizophrenia (SZs) as well as to explore the influence of task load on these networks between HCs and SZs.Participants and Methods:Analyses focused on a secondary dataset comprising Blood Oxygen-Level Dependent (BOLD) data collected from 25 HCs and 27 SZs who completed a working memory (WM) task (N-back) with 5 load conditions while undergoing functional magnetic resonance imaging (fMRI). Region of interest (ROI) data were analyzed using linear mixed-effects models.Results:Group activation differences were found in the posterior salience network (pSN), default mode network (DMN), dorsal default mode network (dDMN), and ventral default mode network (vDMN) showing greater activity for SZs. Specifically, pSN, DMN, dDMN, and vDMN all showed increased activity in SZs compared to HCs. The curve of brain activity was consistent between HCs and SZs with the exception of the vDMN, where HCs show greater activation at modest mental workload (quadratic curve) and SZs showed greater brain activation at lower mental workload (linear). In the CEN, there were no group differences, and the response curve was the same for both groups.Conclusions:These group differences demonstrate network difference between HCs and SZs and could show value in treatments targeting cognitive deficits in SZs from a large-scale brain network connectivity perspective. Future studies are needed to confirm these results with larger sample size in order to examine potential subtleties of interactions between these networks.

How good are virtual hands? Influences of input modality on motor tasks in virtual reality

Hand-tracking enables controller-free interaction with virtual environments, which can make virtual reality (VR) experiences more natural and immersive. As naturalness hinges on both technological and human influence factors, fine-tuning the former while assessing the latter can be used to increase overall experience. This paper investigates a reach-grab-place task inside VR using two input modalities (hand-tracking vs. handheld-controller). Subjects (N = 33) compared the two input methods available on a consumer grade VR headset for their effects on objective user performance and subjective experience of the perceived sense of presence, cognitive workload, and ease-of-use. We found that virtual hands (with hand-tracking) did not influence the subjective feelings of perceived presence, naturalness, & engagement; neither did it inspire the overall ease-of-use while performing the task. In fact, subjects completed the task faster and felt a lower mental workload and higher overall usability with handheld-controllers. The result found that in this particular case, hand-tracking did not improve the psychological and emotional determinants of immersive VR experiences. The study helps expand on our understanding of the two input modalities in terms of their viability for naturalistic experiences in VR akin to real-world scenarios.

Are Eating and Phone Use Equally Distracting? A Simulated Driving Model Comparison

In this study, we sought to compare the mental workload of eating/drinking and phone use while driving. This was done by using Micro Saint Sharp to model a simulated driving task that included stop lights combined with either eating and drinking or a phone call. We hypothesized that the mental workload for phone use and eating/drinking would be the same, as literature suggests that eating while driving can be equally dangerous. Results show that eating and drinking were associated with a lower mental workload than phone use, and both eating and drinking are associated with significantly higher workload than baseline. This research has the potential to inform future legislation regarding driver safety.

Enhanced Interactivity in VR-based Telerobotics: An Eye-tracking Investigation of Human Performance and Workload

Virtual Reality (VR) is gaining ground in the robotics and teleoperation industry, opening new prospects as a novel computerized methodology to make humans interact with robots. In contrast with more conventional button-based teleoperations, VR allows users to use their physical movements to drive robotic systems in the virtual environment. The latest VR devices are also equipped with integrated eye-tracking, which constitutes an exceptional opportunity for monitoring users’ workload online. However, such devices are fairly recent, and human factors have been consistently marginalized so far in telerobotics research. We thus covered these aspects by analyzing extensive behavioral data during simulated guidance of an industrial robot in VR through a pick-and-place task. Users drove the robot via button-based and action-based controls and under low (single-task) and high (dual-task) mental demands. We collected self-reports, performance and eye-tracking data. Specifically, we asked i) how the interactive features of VR affect users’ performance and workload, and additionally tested ii) the sensibility of diverse eye parameters in monitoring users’ vigilance and workload throughout the task. Users performed faster and more accurately, while also showing a lower mental workload, when using an action-based VR control. Among the eye parameters, pupil size was the most resilient indicator of workload, as it was highly correlated with the self-reports and was not affected by the user's degree of physical motion in VR. Our results bring a fresh human-centric overview of human-robot interactions in VR, and systematically demonstrate the potential of VR devices for monitoring human factors in telerobotics contexts.

Influence of Spatial Perception Ability on Virtual Annotation Response in Teleoperation of Excavator

Virtual annotation (VA) for compromising visual limitations during teleoperation can provide critical instructional information, but it remains to be verified whether an operator can respond to VA timely and accurately while operating. Studies have demonstrated a positive relationship between spatial perception ability (SPA) and teleoperating performance. Many studies considered that those with greater SPA have a lower mental workload and more attention on other matters. Therefore, this study sought to examine whether an operator with greater SPA can respond better to VA. Quantitative results from the SPA test questionnaire and the teleoperated excavator experiment showed a significant inverse relationship between SPA and the response time. It is expected that the results could improve the effectiveness of selecting teleoperators and optimize prior management.

A tool for measuring mental workload during prosthesis use: The Prosthesis Task Load Index (PROS-TLX).

When using a upper-limb prosthesis, mental, emotional, and physical effort is often experienced. These have been linked to high rates of device dissatisfaction and rejection. Therefore, understanding and quantifying the complex nature of workload experienced when using, or learning to use, a upper-limb prosthesis has practical and clinical importance for researchers and applied professionals. The aim of this paper was to design and validate a self-report measure of mental workload specific to prosthesis use (The Prosthesis Task Load Index; PROS-TLX) that encapsulates the array of mental, physical, and emotional demands often experienced by users of these devices. We first surveyed upper-limb prosthetic limb users who confirmed the importance of eight workload constructs taken from published literature and previous workload measures. These constructs were mental demands, physical demands, visual demands, conscious processing, frustration, situational stress, time pressure and device uncertainty. To validate the importance of these constructs during initial prosthesis learning, we then asked able-bodied participants to complete a coin-placement task using their anatomical hand and then using a myoelectric prosthesis simulator under low and high mental workload. As expected, using a prosthetic hand resulted in slower movements, more errors, and a greater tendency to visually fixate the hand (indexed using eye-tracking equipment). These changes in performance were accompanied by significant increases in PROS-TLX workload subscales. The scale was also found to have good convergent and divergent validity. Further work is required to validate whether the PROS-TLX can provide meaningful clinical insights to the workload experienced by clinical users of prosthetic devices.

Effects of Noise Exposure and Mental Workload on Physiological Responses during Task Execution.

Twelve healthy male students were recruited to investigate the physiological response to different noise exposure and mental workload (MW) conditions, while performing multi-attribute task battery (MATB) tasks. The experiments were conducted under three noise exposure conditions, with different sound pressure levels and sharpness. After adaptation to each noise condition, the participants were required to perform the resting test and the MATB task tests with low, medium, and high MW. The electroencephalogram (EEG), electrocardiogram (ECG), and eye movement data were obtained, during the periods when participants were in the resting and task taking state. The results showed that subjects’ physiological responses at rest were unaffected by noise exposure conditions. However, during the execution of MATB tasks, the elevated sound pressure level and increased sharpness were significantly correlated with increased mean pupil diameter and heart rate variability (HRV). These responses suggested that the human body defends itself through physiological regulation when noise causes adverse effects. If the negative effects of noise were more severe, this could damage the body’s health and result in a significant drop in task performance. The elevated mental demands led to increased stress on the subjects, which was reflected in a considerable increase in theta relative power. Either high or low MW was related with reduced saccade amplitude and a decrease in weighted task performance, indicating an inverted U-shaped relationship between workload level and work performance.

Feasibility Testing of Tubes@HOME: A Mobile Application to Support Family-Delivered Enteral Care.

Assistance from medical devices is common for children with medical complexity (CMC) but introduces caregiving challenges. We tested the feasibility of "Tubes@HOME," a mobile application supporting CMC family-delivered care using enteral care as a model. Caregivers of CMC with enteral tubes participated in a 30-day feasibility study of Tubes@HOME November 2020 through January 2021. Tubes@HOME was available on mobile devices and designed to support collaborative care and tracking over time. Key features include child profile, caregiving network management, care routines, feedback loop, and action plans. Care routines delineated nutrition, medication, and procedural tasks needed for the child: frequencies, completions, and reminders. Metadata summarized feature use among users. Feasibility was evaluated with postuse questionnaires and interviews. Measures of Tubes@HOME's usability and usefulness included the NASA Task Load Index (TLX), System Usability Scale (SUS), and Acceptability and Use of Technology Questionnaire (AUTQ). Among n = 30 children, there were 30 primary (eg, parent) and n = 22 nonprimary caregivers using Tubes@HOME. Children had a median (IQR) 10 (5.5-13) care routines created. For care routines created, 93% were marked complete at least once during the study period, with participants engaging with routines throughout study weeks 2 to 4. Results (mean [SD]) indicated low mental workload (TLX) 30.9 (12.2), good usability (SUS) 75.4 (14.7), and above-average usefulness (AUTQ) 4.0 (0.7) associated with Tubes@HOME, respectively. Interviews contextualized usefulness and suggested improvements. Longitudinal use of Tubes@HOME among caregiving networks appeared feasible. Efficacy testing is needed, and outcomes could include reliability of care delivered in home and community.

Cognitive performance and electroencephalographic variations in air traffic controllers under various mental workload and time of day

The aim of this study was to investigate the effects of mental workload (MWL) and time of day on cognitive performance and electroencephalographic (EEG) parameters of air traffic controllers. EEG signals recorded while 20 professional air traffic controllers performed cognitive tasks [A-X Continuous Performance Test (AX-CPT) and 3-back working memory task] after they were exposed to two levels of task difficulty (high and low MWL) in the morning and afternoon. Significant decreases in cognitive performance were found when the levels of task difficulty increased in both tasks. The results confirmed the sensitivity of the theta and beta activities to levels of task difficulty in the 3-back task, while they were not affected in the AX-CPT. Theta and beta activities were influenced by time of day in the AX-CPT. The findings provide guidance for application of changes in EEG parameters when MWL level is manipulated during the day that could be implemented in future for the development of real-time monitoring systems to improve aviation safety.

Evaluating mental workload during multitasking in simulated flight.

BackgroundPilots must process multiple streams of information simultaneously. Mental workload is one of the main issues in man–machine interactive mode when dealing with multiple tasks. This study aimed to combine functional near‐infrared spectroscopy (fNIRS) and electrocardiogram (ECG) to detect changes in mental workload during multitasking in a simulated flight.MethodsTwenty‐six participants performed three multitasking tasks at different mental workload levels. These mental workload levels were set by varying the number of subtasks. fNIRS and ECG signals were recorded during tasks. Participants filled in the national aeronautics and space administration task load index (NASA‐TLX) scale after each task. The effects of mental workload on scores of NASA‐TLX, performance of tasks, heart rate (HR), heart rate variability (HRV), and the prefrontal cortex (PFC) activation were analyzed.ResultsCompared to multitasking in lower mental workload conditions, participants exhibited higher scores of NASA‐TLX, HR, and PFC activation when multitasking in high mental workload conditions. Their performance was worse during the high mental workload multitasking condition, as evidenced by the higher average tracking distance, smaller number of response times, and longer response time of the meter. The standard deviation of the RR intervals (SDNN) was negatively correlated with subjective mental workload in the low task load condition and PFC activation was positively correlated with HR and subjective mental workload in the medium task load condition.ConclusionHR and PFC activation can be used to detect changes in mental workload during simulated flight multitasking tasks.

Effects of automation trust in drivers' visual distraction during automation.

With ongoing improvements in vehicle automation, research on automation trust has attracted considerable attention. In order to explore effects of automation trust on drivers’ visual distraction, we designed a three-factor 2 (trust type: high trust group, low trust group) × 2 (video entertainment: variety-show videos, news videos) × 3 (measurement stage: 1–3) experiment. 48 drivers were recruited in Dalian, China for the experiment. With a driving simulator, we used detection-response tasks (DRT) to measure each driver’s performance. Their eye movements were recorded, and automation-trust scale was used to divide participants into high trust group and low trust group. The results show that: (1) drivers in the high trust group has lower mental workload and paid more attention to visual non-driving-related tasks; (2) video entertainment also has an impact on distraction behavior, variety-show videos catch more attention than news videos. The findings of the present study indicate that drivers with high automation trust are more likely to be involved in non-driving-related visual tasks.

Effects of unreliable automation and takeover time budget on young drivers’ mental workload

Young drivers are involved in a significantly higher number of crashes than any other age group. Highly automated vehicles are expected to improve traffic safety and reduce human errors; however, driver needs to take over in situations where the automation fails. A driving simulation study was conducted with twenty-eight young drivers to investigate the effects of unreliable automation, different takeover time budgets (TOTBs), and secondary tasks on mental workload during takeover situations. Mental workload was measured using a combination of physiological and secondary task performance measures. Results suggested that when faced with critical incidents, young drivers experienced lower mental workload under 10s of TOTB as compared to 5s or 8s of TOTB especially when they were engaged in a demanding secondary task. In addition, drivers experienced higher mental workload when regaining the control of the vehicle in the automated mode than the manual driving condition.