Tactile detection response task: Metrics for assessing drivers’ cognitive workload

The Tactile Detection Response Task (TDRT) has been used to assess the cognitive workload of driver distraction with response time and miss rate as metrics of cognitive workload. However, it is not clear which metric is more sensitive and whether sensitivity is maintained for visual tasks. The objective of this study was to assess the sensitivity of the TDRT to changes in cognitive workload and to examine whether the sensitivity depends on task modality. A driving simulator study was conducted with 24 participants. The study included restaurant selection tasks with three presentation modalities (auditory, visual, and hybrid) and two difficulty levels (low and high). The high difficulty level was designed to be more cognitively demanding than the low difficulty level. Mixed-effects models were applied to examine the TDRT metrics and task difficulty level. The model controlled for age group, gender, and included a random effect for participants. The high difficulty level of the auditory tasks significantly increased the likelihood of missing a TDRT stimulus. No statistically significant differences were observed for visual and hybrid tasks. TDRT response time was not significantly associated with the difficulty level, regardless of task modality. In this study, the binary outcome TDRT miss was thus considered a more sensitive metric of cognitive workload than TDRT response time. TDRT response time can still be used to measure cognitive workload when tasks are relatively easy and the TDRT miss rate is close to zero. In addition, the sensitivity of the TDRT miss diminished for tasks that involved a visual component. Researchers who use TDRT to measure the cognitive workload associated with visual tasks should be aware of this limitation.     

Evidence for the role of personality in the cognitive performance of older male drivers

ObjectivesThis study aimed to examine whether in older male drivers the level of information processing under increasing cognitive workload varies with the level of personality traits.MethodThe study involved 60 male, active drivers aged between 65 and 81 (M = 71, SD = 4.4). During passive driving they performed central (a test in the n-back scheme, in three cognitive workload levels) and peripheral (memorizing objects characteristic for road traffic) tasks presented simultaneously in the central and peripheral visual fields. A wide-angle high-fidelity collimated visual system was used to display visual stimuli. In the central task, the reaction time and its correctness were measured, while the peripheral task measured the number of memorized objects. The EPQ-R questionnaire was used to assess personality traits, and the memory functions were assessed using the MMSE test.ResultsAs the central task-induced cognitive workload increases, the performance of both central and peripheral tasks deteriorates. These tasks were performed less accurately by drivers with a higher level of psychoticism than those with a lower level of this trait. This dependency related to all levels of cognitive workload. In contrast, the drivers with a higher level of neuroticism showed a lower level of performance of the peripheral task than those with a low level of this trait. This dependency concerned only the central task with a medium cognitive workload.ConclusionThe level of personality traits, especially the ones related to the emotional sphere, contributed to the decrease in the effectiveness of action (longer reaction time, increase in the number of errors, decrease in the number of memorized objects) in the conditions of increasing cognitive workload. A higher level of neuroticism and psychoticism can be conducive to making errors on the road. This applies especially to situations that pose high demands on the driver’s cognitive system.     

Workload and burnout in nurses

This paper examines the relationship between workload, burnout and somatization in nurses. The respondents consisted of 1363 nurses employed in hospitals, which were undergoing extensive restructuring. Results of structural equation analyses showed that workload was positively related to emotional exhaustion. Emotional exhaustion led to cynicism and somatization, and cynicism was negatively related to nurses' professional efficacy. Implications of the results for nursing practice are discussed. Copyright © 2001 John Wiley & Sons, Ltd.     

Temporal fluctuations in driving demand: The effect of traffic complexity on subjective measures of workload and driving performance

Traffic density has been shown to be a factor of traffic complexity which influences driver workload. However, little research has systematically varied and examined how traffic density affects workload in dynamic traffic conditions. In this driving simulator study, the effects of two dynamically changing traffic complexity factors (Traffic Flow and Lane Change Presence) on workload were examined. These fluctuations in driving demand were then captured using a continuous subjective rating method and driving performance measures. The results indicate a linear upward trend in driver workload with increasing traffic flow, up to moderate traffic flow levels. The analysis also showed that driver workload increased when a lane change occurred in the drivers’ forward field of view, with further increases in workload when that lane change occurred in close proximity. Both of these main effects were captured via subjective assessment and with driving performance parameters such as speed variation, mean time headway and variation in lateral position. Understanding how these traffic behaviours dynamically influence driver workload is beneficial in estimating and managing driver workload. The present study suggests possible ways of defining the level of workload associated with surrounding traffic complexity, which could help contribute to the design of an adaptive workload estimator.     

Effects of specific emotions on subjective judgment,driving performance,and perceived workload

The aim of this paper was to explore effects of specific emotions on subjective judgment, driving performance, and perceived workload. The traditional driving behavior research has focused on cognitive aspects such as attention, judgment, and decision making. Psychological findings have indicated that affective states also play a critical role in a user’s rational, functional, and intelligent behaviors. Most applied emotion research has concentrated on simple valence and arousal dimensions. However, recent findings have indicated that different emotions may have different impacts, even though they belong to the same valence or arousal. To identify more specific affective effects, seventy undergraduate participants drove in a vehicle simulator under three different road conditions, with one of the following induced affective states: anger, fear, happiness, or neutral. We measured their subjective judgment of driving confidence, risk perception, and safety level after affect induction; four types of driving errors: Lane Keeping, Traffic Rules, Aggressive Driving, and Collision while driving; and the electronic NASA-TLX after driving. Induced anger clearly showed negative effects on subjective safety level and led to degraded driving performance compared to neutral and fear. Happiness also showed degraded driving performance compared to neutral and fear. Fear did not have any significant effect on subjective judgment, driving performance, or perceived workload. Results suggest that we may need to take emotions and affect into account to construct a naturalistic and generic driving behavior model. To this end, a specific-affect approach is needed, beyond the sheer valence and arousal dimensions. Given that workload results are similar across affective states, examining affective effects may also require a different approach than just the perceived workload framework. The present work is expected to guide emotion detection research and help develop an emotion regulation model and adaptive interfaces for drivers.     

Measuring drivers’ takeover performance in varying levels of automation: Considering the influence of cognitive secondary task

Mixed control by driver and automated system will remain in use for decades until fully automated driving is perfected. Thus, drivers must be able to accurately regain control of vehicles in a timely manner when the automated system sends a takeover request (TOR) at its limitation. Therefore, determining the factors that affect drivers’ takeover quality at varying levels of automated driving is important. Previous studies have shown that visually distracting secondary tasks impair drivers’ takeover performance and increase the subjective workload. However, the influence of purely cognitive distracting secondary tasks on drivers’ takeover performance and how this influence varies at different levels of automation are still unknown. Hence, a 5 (driving modes) × 3 (cognitive secondary tasks) factorial design with the within-subject factors was adopted for this driving simulator experiment. The sample consisted of 21 participants. The participants’ subjective workloads were recorded by the NASA-Task Load Index (NASA-TLX). Results showed that compared to manual driving conditions, the drivers’ subjective workloads were significantly reduced in both partially and highly automated driving conditions, even with a TOR, confirming the benefit of the automated driving system in terms of reducing the driving workload. Moreover, the drivers exhibited a lower takeover behavior quality at high levels of automation than manual driving in terms of increased reaction time, abnormal performance, standard deviation of lane position, lane departure probability, and reduced minimum of time to collision. However, at the highly automated driving condition, the drivers’ longitudinal driving safety and ability to follow instructions improved when performing a highly cognitive secondary task. This phenomenon possibly occurred because automated driving conditions lead to an underload phenomenon, and the execution of highly cognitive tasks transfers drivers into moderate load, which helps with the drivers’ takeover performance.     

The Stationary-Gaze Task Should Not Be Systematically Used as the Control Task in Studies of Postural Control

In studies of postural control, a control task is often used to understand significant effects obtained with experimental manipulations. This task should be the easiest task and (therefore) engage the lowest behavioral variability and cognitive workload. Since 1983, the stationary-gaze task is considered as the most relevant control task. Instead, the authors expected that free looking at small targets (white paper or images; visual angle: 12°) could be an easier task. To verify this assumption, 16 young individuals performed stationary-gaze, white-panel, and free-viewing 12° tasks in steady and relaxed stances. The stationary-gaze task led to significantly higher cognitive workload (mean score in the National Aeronotics and Space Administration Task Load Index questionnaire), higher interindividual body (head, neck, and lower back) linear variability, and higher interindividual body angular variability—not systematically yet—than both other tasks. There was more cognitive workload in steady than relaxed stances. The authors also tested if a free-viewing 24° task could lead to greater angular displacement, and hence greater body sway, than could the other tasks in relaxed stance. Unexpectedly, the participants mostly moved their eyes and not their body in this task. In the discussion, the authors explain why the stationary-gaze task may not be an ideal control task and how to choose this neutral task.     

数据-笔墨比率对过程监控任务绩效的影响

以24名参加飞行员心理选拔的大学生为被试,采用模拟过程监控任务,以反应时、心理负荷与情境意识为指标,考察了数据-笔墨比率在动态图形显示设计中的应用。研究结果表明,低数据-笔墨比率显示条件下的反应时较短、情境意识较高,即适当增加表达数据点之间关系的笔墨虽然会降低数据一笔墨比率,但有助于监控绩效。实验结果说明,在将静态图形显示的设计原则运用于动态显示设计时,应对其适用性进行检测。     

Situation Awareness and Workload in Aviation

A pilot faces special challenges imposed by the need to control a multivariate lagged system in a heterogeneous multitask environment. The time lags between critical variables require prediction in an uncertain world. The interrelated concepts of situation awareness and workload are central to aviation psychology. Three components of situation awareness are spatial awareness, system awareness, and task awareness. Each of these components has real–world implications, spatial awareness for instrument displays, system awareness for keeping the operator informed about actions that have been taken by automated systems, and task awareness for attention and task management. Task management is directly related to mental workload, as the competing demands of tasks for attention exceed the operator's limited resources.