Attentional models of multitask pilot performance using advanced display technology

Expectancy or Salience?-Replicating Senders' Dial-Monitoring Experiments With a Gaze-Contingent Window

INTRODUCTION

In the 1950s and 1960s, John Senders carried out a number of influential experiments on the monitoring of multidegree-of-freedom systems. In these experiments, participants were tasked with detecting events (threshold crossings) for multiple dials, each presenting a signal with different bandwidth. Senders' analyses showed a nearly linear relationship between signal bandwidth and the amount of attention paid to the dial, and he argued that humans sample according to bandwidth, in line with the Nyquist-Shannon sampling theorem.

OBJECTIVE

The current study tested whether humans indeed sample the dials based on bandwidth alone or whether they also use salient peripheral cues.

METHODS

A dial-monitoring task was performed by 33 participants. In half of the trials, a gaze-contingent window was used that blocked peripheral vision.

RESULTS

The results showed that, without peripheral vision, humans do not effectively distribute their attention across the dials. The findings also suggest that, when given full view, humans can detect the speed of the dial using their peripheral vision.

CONCLUSION

It is concluded that salience and bandwidth are both drivers of distributed visual attention in a dial-monitoring task.

APPLICATION

The present findings indicate that salience plays a major role in guiding human attention. A subsequent recommendation for future human-machine interface design is that task-critical elements should be made salient.

Visual behavior of racing bike cyclists in multi-tasking situations

Distracted biking can have serious repercussions for the rider such as accidents. The purpose of the present experiment was to determine the effect of visually monitoring two parameters, the cadence, and the heart rate on a bike computer fixed on a racing bike, and simultaneously detect hazardous traffic situations. Individuals (n = 20) were instructed to ride a racing bike that was fitted onto a roller trainer. After conducting a bicycle step test to assess the maximal heart rate (HFmax), participants were assigned to a within subject-design on a separate day. They were instructed to perform the riding task in two single-task conditions (only watching the traffic at the video with occluded or without occluded bike computer), two multi-tasking conditions (monitoring the cadence of 70 RPM or 90 RPM, monitoring the heart rate, and observing the traffic) and one control condition (no instructions). Percentage dwell time of the eye movements, the constant error from the target cadence, keeping the heart rate in an interval of 50% - 70% of the HFmax, and percentage of the recognized hazard traffic situations were analyzed. The analysis indicated that monitoring the parameters on the bike computer induced no significant decline in perceived hazardous traffic situations.

A Review of Human Performance Models for Prediction of Driver Behavior and Interactions With In-Vehicle Technology

OBJECTIVE

This study investigated the use of human performance modeling (HPM) approach for prediction of driver behavior and interactions with in-vehicle technology.

BACKGROUND

HPM has been applied in numerous human factors domains such as surface transportation as it can quantify and predict human performance; however, there has been no integrated literature review for predicting driver behavior and interactions with in-vehicle technology in terms of the characteristics of methods used and variables explored.

METHOD

A systematic literature review was conducted using Compendex, Web of Science, and Google Scholar. As a result, 100 studies met the inclusion criteria and were reviewed by the authors. Model characteristics and variables were summarized to identify the research gaps and to provide a lookup table to select an appropriate method.

RESULTS

The findings provided information on how to select an appropriate HPM based on a combination of independent and dependent variables. The review also summarized the characteristics, limitations, applications, modeling tools, and theoretical bases of the major HPMs.

CONCLUSION

The study provided a summary of state-of-the-art on the use of HPM to model driver behavior and use of in-vehicle technology. We provided a table that can assist researchers to find an appropriate modeling approach based on the study independent and dependent variables.

APPLICATION

The findings of this study can facilitate the use of HPM in surface transportation and reduce the learning time for researchers especially those with limited modeling background.

Evaluation of traffic signs information volume at highway tunnel entrance zone based on the visual sample entropy of novice and experienced drivers

OBJECTIVE

Traffic signs play a crucial role in ensuring road traffic safety, particularly in high-risk driving zones like the entrance zone of highway tunnels. However, the impact of traffic signs information volume (TSIV) on the performance of experienced and novice drivers in this specific zone remains unclear. This study aims to investigate the influence of TSIV on the visual sample entropy (SampEn) of both experienced and novice drivers in the entrance zone of highway tunnels.

METHODS

A real vehicle driving trial was conducted with 60 participants approaching tunnels under various TSIV conditions. Fixation duration SampEn, saccade duration SampEn, and saccade amplitude SampEn were analyzed for both driver groups.

RESULTS

As both driver groups approached the tunnel entrance, fixation duration SampEn, saccade duration SampEn, and saccade amplitude SampEn gradually increased. Initially, visual SampEn declined, followed by an increase as the TSIV level increased. The lowest value of visual SampEn was observed under the T3 TSIV condition (48.31 bits). Experienced drivers exhibited lower visual SampEn compared to novice drivers under similar TSIV conditions.

CONCLUSIONS

TSIV and driving experience significantly influence the visual SampEn of drivers approaching the tunnel entrance. Optimal visual search patterns and performance were observed under the T3 TSIV condition (48.31 bits), which is critical for ensuring driving safety in the entrance zone of highway tunnels. Additionally, experienced drivers demonstrate better adaptation to tunnel environments and TSIV, while novice drivers may benefit from additional training to enhance their visual perception and performance.

Attention to Changes on a Head-Worn Display: Two Preclinical Studies with Healthcare Scenarios

OBJECTIVE

In two experiments, we examined how quickly different visual alerts on a head-worn display (HWD) would capture participants' attention to a matrix of patient vital sign values, while multitasking.

BACKGROUND

An HWD could help clinicians monitor multiple patients, regardless of where the clinician is located. We sought effective ways for HWDs to alert multitasking wearers to important events.

METHODS

In two preclinical experiments, university student participants performed a visuomotor tracking task while simultaneously monitoring simulated patient vital signs on an HWD to detect abnormal values. Methods to attract attention to abnormal values included highlighting abnormal vital signs and imposing a white flash over the entire display.

RESULTS

Experiment 1 found that participants detected abnormal values faster with high contrast than low contrast greyscale highlights, even while performing difficult tracking. In Experiment 2, a white flash of the entire screen quickly and reliably captured attention to vital signs, but less so on an HWD than on a conventional screen.

CONCLUSION

Visual alerts on HWDs can direct users' attention to patient transition events (PTEs) even under high visual-perceptual load, but not as quickly as visual alerts on fixed displays. Aspects of the results have since been tested in a healthcare context.

APPLICATION

Potential applications include informing the design of HWD interfaces for monitoring multiple processes and informing future research on capturing attention to HWDs.

Guiding Attention via a Cognitive Aid During a Simulated In-Hospital Cardiac Arrest Scenario: A Salience Effort Expectancy Value Model Analysis

OBJECTIVE

To investigate the effect of a cognitive aid on the visual attention distribution of the operator using the Salience Effort Expectancy Value (SEEV) model.

BACKGROUND

Cognitive aids aim to support an operator during the execution of a task. The effect of cognitive aids on performance is frequently evaluated but whether a cognitive aid improved, for example, attention distribution has not been considered.

METHOD

We built the Expectancy Value (EV) model version which can be considered to indicate optimal attention distribution for a given event. We analyzed the eye tracking data of emergency physicians while using a cognitive aid application versus no application during a simulated in-hospital cardiac arrest scenario.

RESULTS

The EV model could fit the attention distribution in such a simulated emergency situation. Partially supporting our hypothesis, the cognitive aid application group showed a significantly better EV model fit than the no application group in the first phases of the event, but a worse fit in the last phase.

CONCLUSION

We demonstrated that a cognitive aid affected attention distribution and that the SEEV model provides the means of capturing these effects. We suggest that the aid supported and improved visual attention distribution in the stressful first phases of a cardiopulmonary resuscitation but may have focused attention on objects that are relevant for lower priority goals in the last phase.

APPLICATION

The SEEV model can provide insights into expected and unexpected effects of cognitive aids on visual attention distribution and may help to design better artifacts.

Visual behavior and road traffic hazard situations when using a bike computer on a racing bike: An eye movement study

Bike computers are an important equipment, especially on race bikes where athletes can monitor output parameters. The purpose of the present experiment was to determine the effect of visually monitoring the cadence of a bike computer and to perceive hazard traffic situations in a virtual environment. In a within subject-design individuals (N = 21) were instructed to perform the riding task in two single-task conditions (only watching the traffic at the video with occluded or without occluded bike computer), two dual-task conditions (monitoring the cadence of 70 RPM or 90 RPM and observing the traffic) and one control condition (no instructions). Percentage dwell time of the eye movements, the constant error from the target cadence, and percentage of the recognized hazard traffic situations were analyzed. The analysis indicated that the visual behavior to monitor the traffic was not reduced when individuals used a bike computer to control the cadence.

Head-mounted display versus computer monitor for visual attention screening: A comparative study

Visual attention is crucial to many tasks during working. When it is impaired, the risk of occupational accidents is increased. A potential accident prevention would be the tracking of employees' attentional states to construct break regimes. There is a promising visual attention test administered on a computer monitor (CM) that has several advantages over widely used continuous performance tests in detecting inattentiveness in occupational environments. However, as the setup with a CM is impractical for the use in particular working environments (e.g., lack of space or disturbing exposure to light), the test was implemented into a head-mounted display (HMD). This study aimed to investigate whether the HMD version of the test is a suitable alternative to the CM version. For this purpose, participants (N = 30; 20-29 y) performed both tests. The performance on the HMD was significantly lower than on the CM. Moreover, the performances were compared with normative data recorded with a CM in a previous study. These data significantly differ from the data recorded with the CM in the present study. This emphasizes the importance of a standardized test environment, which could be provided by an HMD. Conclusively, this study revealed that the new VR tool, based on a previous test designed to assess visual skills in a complex visual environment, exhibited good psychometric property regarding the reliability. In additional, no problems were revealed regarding the functionality and usability of the HMD.

Development of a metric to evaluate the ergonomic principles of assistive systems, based on the DIN 92419

The DIN 92419 defines six principles for assistive systems' ergonomic design. There is, however, a lack of measurement tools to evaluate assistive systems considering these principles. Consequently, this study developed a measurement tool for the quantitative evaluation of the fulfilment of each principle for assistive systems. A systematic literature review was performed to identify dimensions belonging to the principles, identify how previous research evaluated these dimensions, and develop a measurement tool for assistive systems. Findings show that scales commonly used for evaluating assistive systems disregard several aspects highlighted as relevant by research, implying the need for considering the DIN 92419 principles. Based on established scales and theoretical findings, a questionnaire, and a checklist for evaluating assistive systems were developed. The work provides a grounding for measuring relevant aspects of assistive systems. Further development is needed to substantiate the reliability and validity of the proposed questionnaire scales and items. Practitioner Summary: Responding to the gap of a holistic measurement tool to evaluate assistive systems, a systematic literature review was performed considering the DIN 92419 principles. This resulted in a comprehensive summary of relevant aspects of assistive systems that were made numerically measurable, which proposes better criteria to assess assistive systems. Abbreviations: IoT: internet of things; RQ: research question; TAM: technology acceptance model; UTAUT: unified theory of acceptance and use of technology; AaaS: adaptivity as a service; SAR: socially assistive robots; SEEV: salience, effort, expectancy, and value; PRISMA: preferred reporting items for systematic reviews and meta-analyses; HMI: human-machine interaction; HRI: human-robot interaction; BCI: brain-computer interface; QUEST: Quebec user evaluation of satisfaction with assistive technology; SUS: system usability scale; NASA-TLX: NASA task load index; ATD PA: assistive technology device predisposition assessment; Wheel Con: wheelchair use confidence scale; CATOM: caregiver assistive technology outcome measure; CBI: caregiver burden inventory; RoSAS: robotic social attributes scale; WheelCon: wheelchair use confidence scale; IMI: intrinsic motivation inventory; ATD PA: assistive technology device predisposition assessment; UEQ: User experience questionnaire; USEUQ: usefulness satisfaction and ease of use questionnaire; USPW: usability scale for power wheelchairs; UES: user engagement scale; SUTAQ: service user technology acceptability questionnaire; QUEAD: questionnaire for the evaluation of physical assistive devices; FATCAT: functional assessment tool for cognitive assistive technology; SE-HRI: human-robot interaction scale; SART: situation awareness rating technique; TSQ;WT: tele-healthcare satisfaction questionnaire-wearable technology; PAIF: participants' assessment of the intervention's feasibility; SWAT: subjective workload assessment technique; MARS-HA: measure of audiologic rehabilitation self-efficacy for hearing aids; IOI-HA: International outcome inventory for hearing aids; FMA: functional mobility assessment; FBIS: familiarity and behavioural intention survey; CSQ: client satisfaction questionnaire; COPM: canadian occupational performance measure; ATCS: assistive technology confidence scale; ACC: acceptance; SSP: safety, security and privacy; OPT: optimisation of resultant internal load; CTRL: controllability; ADAPT: adaptability; P&I: perceptibility and identifiability; AAL: ambient assisted living; VR: virtual reality; AS: assistive system; WEIRD: Western, educated, industrialised, rich, and democratic; HEART: horizontal european activities of rehabilitation technology; AAATE: advancement of assistive technology in Europe's; GATE: global collaboration on assistive technology; ATA-C: assistive technology assessment toolkit.

Deficits in visuospatial attentional cueing following mild traumatic brain injury

Visual attentional deficits are frequently reported in patients with mild traumatic brain injury (TBI). In the present study, the ability to orient visual attention (i.e., the use of endogenous and exogenous visual cues) was investigated using a modified Posner visual search task, in which the participant was required to search for a target shape (radial frequency patterns) amongst distractor shapes. Participants were required to determine whether a target radial frequency pattern was present or absent from an array of distractors. Attention to the target location was cued using central or peripheral cueing procedures to investigate endogenous or exogenous attention allocation. Predictability was not manipulated between central and peripheral cues. Search difficulty was varied by systematically changing the radial frequency difference between target and distractors (and thereby shape difference), and cues could be valid or invalid in that they correctly or incorrectly indicated the position of the target shape. Both target discriminability (i.e., identifying the presence or absence of the target) and reaction times were measured. Thirteen patients with chronic mild TBI and 21 age-, sex-, and IQ -matched healthy controls participated in the study. For control participants, both discrimination accuracy and reaction times improved with visual search efficiency, and they were sensitive to the type of cue, with performance worst for cue invalid conditions than valid conditions. However, the results for TBI patients were strikingly different; we find that discrimination accuracy slightly improved with visual search difficulty (compared to controls), but not reaction times, and TBI patients were largely insensitive to the type of visual cue, and did not show a selective deficit for central or peripheral cues, suggesting an impairment in both endogenous and exogenous visual attention. In conclusion, patients with mild TBI exhibit a poor ability to orient visual attention.

The Validity of the SEEV Model as a Process Measure of Situation Awareness: The Example of a Simulated Endotracheal Intubation

OBJECTIVE

In the context of anesthesiology, we investigated whether the salience effort expectancy value (SEEV) model fit is associated with situation awareness and perception scores.

BACKGROUND

The distribution of visual attention is important for situation awareness-that is, understanding what is going on-in safety-critical domains. Although the SEEV model has been suggested as a process situation awareness measure, the validity of the model as a predictor of situation awareness has not been tested.

METHOD

In a medical simulation, 31 senior and 30 junior anesthesiologists wore a mobile eye tracker and induced general anesthesia into a simulated patient. When inserting a breathing tube into the mannequin's trachea (endotracheal intubation), the scenario included several clinically relevant events for situation awareness and general events in the environment. Both were assessed using direct awareness measures.

RESULTS

The overall SEEV model fit was good with no difference between junior and senior anesthesiologists. Overall, the situation awareness scores were low. As expected, the SEEV model fits showed significant positive correlations with situation awareness level 1 scores.

CONCLUSION

The SEEV model seems to be suitable as a process situation awareness measure to predict and investigate the perception of changes in the environment (situation awareness level 1). The situation awareness scores indicated that anesthesiologists seem not to perceive the environment well during endotracheal intubation.

APPLICATION

The SEEV model fit can be used to capture and assess situation awareness level 1. During endotracheal intubation, anesthesiologists should be supported by technology or staff to notice changes in the environment.

Modeling eye movement in dynamic interactive tasks for maximizing situation awareness based on Markov decision process

For complex dynamic interactive tasks (such as aviating), operators need to continuously extract information from areas of interest (AOIs) through eye movement to maintain high level of situation awareness (SA), as failures of SA may cause task performance degradation, even system accident. Most of the current eye movement models focus on either static tasks (such as image viewing) or simple dynamic tasks (such as video watching), without considering SA. In this study, an eye movement model with the goal of maximizing SA is proposed based on Markov decision process (MDP), which is designed to describe the dynamic eye movement of experienced operators in dynamic interactive tasks. Two top-down factors, expectancy and value, are introduced into this model to represent the update probability and the importance of information in AOIs, respectively. In particular, the model regards sequence of eye fixations to different AOIs as sequential decisions to maximize the SA-related reward (value) in the context of uncertain information update (expectancy). Further, this model was validated with a flight simulation experiment. Results show that the predicted probabilities of fixation on and shift between AOIs are highly correlated (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R = 0.928$$\end{document}R=0.928 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R = 0.951$$\end{document}R=0.951, respectively) with those of the experiment data.

Absence of Pilot Monitoring Affects Scanning Behavior of Pilot Flying: Implications for the Design of Single-Pilot Cockpits

OBJECTIVE

This study examines whether the pilot flying's (PF) scanning behavior is affected by the absence of the pilot monitoring (PM) and aims at deriving implications for the design of single-pilot cockpits for commercial aviation.

BACKGROUND

Due to technological progress, a crew reduction from two-crew to single-pilot operations (SPO) might be feasible. This requires a redesign of the cockpit to support the pilot adequately, especially during high workload phases such as approach and landing. In these phases, the continuous scanning of flight parameters is of particular importance.

METHOD

Experienced pilots flew various approach and landing scenarios with or without the support of the PM in a fixed-base Airbus A320 simulator. A within-subject design was used and eye-tracking data were collected to analyze scanning behavior.

RESULTS

The results confirm that the absence of the PM affects the PF's scanning behavior. Participants spent significantly more time scanning secondary instruments at the expense of primary instruments when flying alone. Moreover, the frequency of transitions between the cockpit instruments and the external view increased while mean dwell durations on the external view decreased.

CONCLUSION

The findings suggest that the PM supports the PF to achieve efficient scanning behavior. Information should be presented differently in commercial SPO to compensate for the PM's absence and to avoid visual overload.

APPLICATION

This research will help inform the design of commercial SPO flight decks providing adequate support for the pilot particularly in terms of efficient scanning behavior.

Multitasking in Driving as Optimal Adaptation Under Uncertainty

OBJECTIVE

The objective was to better understand how people adapt multitasking behavior when circumstances in driving change and how safe versus unsafe behaviors emerge.

BACKGROUND

Multitasking strategies in driving adapt to changes in the task environment, but the cognitive mechanisms of this adaptation are not well known. Missing is a unifying account to explain the joint contribution of task constraints, goals, cognitive capabilities, and beliefs about the driving environment.

METHOD

We model the driver's decision to deploy visual attention as a stochastic sequential decision-making problem and propose hierarchical reinforcement learning as a computationally tractable solution to it. The supervisory level deploys attention based on per-task value estimates, which incorporate beliefs about risk. Model simulations are compared against human data collected in a driving simulator.

RESULTS

Human data show adaptation to the attentional demands of ongoing tasks, as measured in lane deviation and in-car gaze deployment. The predictions of our model fit the human data on these metrics.

CONCLUSION

Multitasking strategies can be understood as optimal adaptation under uncertainty, wherein the driver adapts to cognitive constraints and the task environment's uncertainties, aiming to maximize the expected long-term utility. Safe and unsafe behaviors emerge as the driver has to arbitrate between conflicting goals and manage uncertainty about them.

APPLICATION

Simulations can inform studies of conditions that are likely to give rise to unsafe driving behavior.

Effects of full windshield head-up display on visual attention allocation

This study explores the impact of full windshield head-up display (FHUD) cues on the visual attention allocation of drivers under different scenarios. Forty-eight participants with driving experience were randomly divided into two groups and asked to drive on a preset route in various virtual driving scenarios created in advance. The full windshield highlights situational cues related to the driving task, such as lane lines, safe vehicle distance warnings, navigation guidance and pedestrian cues. Regarding the perception of situational cues, the number of fixations and mean fixation duration with FHUD were lower than those without FHUD. Furthermore, the dwell time percentage of the driver's forward view with FHUD was larger than that without FHUD, and the dwell time percentage on both sides was smaller than that without FHUD. In conclusion, FHUD may help drivers more effectively perceive cues and improve drivers' visual attention allocation. Practitioner summary: FHUD may affect drivers' attention while driving. We examined the effect of FHUD on number of fixations, fixation duration and dwell time percentage in the area of interest under different weather scenarios. Experimental results indicated that FHUD could improve drivers' visual attention allocation and help drivers more effectively perceive cues. Abbreviations: FHUD: full windshield head-up display; HUD: head-up display; HDD: head-down display; AOI: area of interests; AR: augmented reality.

Derivation and Demonstration of a New Metric for Multitasking Performance

OBJECTIVE

We proposed and demonstrate a theory-driven, quantitative, individual-level estimate of the degree to which cognitive processes are degraded or enhanced when multiple tasks are simultaneously completed.

BACKGROUND

To evaluate multitasking, we used a performance-based cognitive model to predict efficient performance. The model controls for single-task performance at the individual level and does not depend on parametric assumptions, such as normality, which do not apply to many performance evaluations.

METHODS

Twenty participants attempted to maintain their isolated task performance in combination for three dual-task and one triple-task scenarios. We utilized a computational model of multiple resource theory to form hypotheses for how performance in each environment would compare, relative to the other multitask contexts. We assessed if and to what extent multitask performance diverged from the model of efficient multitasking in each combination of tasks across multiple sessions.

RESULTS

Across the two sessions, we found variable individual task performances but consistent patterns of multitask efficiency such that deficits were evident in all task combinations. All participants exhibited decrements in performing the triple-task condition.

CONCLUSIONS

We demonstrate a modeling framework that characterizes multitasking efficiency with a single score. Because it controls for single-task differences and makes no parametric assumptions, the measure enables researchers and system designers to directly compare efficiency across various individuals and complex situations.

APPLICATION

Multitask efficiency scores offer practical implications for the design of adaptive automation and training regimes. Furthermore, a system may be tailored for individuals or suggest task combinations that support productivity and minimize performance costs.

Visuospatial Attention Allocation as an Indicator of Cognitive Deficit in Traumatic Brain Injury: A Systematic Review and Meta-Analysis

Traumatic Brain Injury (TBI) is defined by changes in brain function resulting from external forces acting on the brain and is typically characterized by a host of physiological and functional changes such as cognitive deficits including attention problems. In the present study, we focused on the effect of TBI on the ability to allocate attention in vision (i.e., the use of endogenous and exogenous visual cues) by systematically reviewing previous literature on the topic. We conducted quantitative synthesis of 16 selected studies of visual attention following TBI, calculating 80 effect size estimates. The combined effect size was large (g = 0.79, p < 0.0001) with medium heterogeneity (I² = 68.39%). Subgroup analyses revealed an increase in deficit with moderate-to-severe and severe TBI as compared to mild TBI [F_{(2, 76)} = 24.14, p < 0.0001]. Task type was another key source of variability and subgroup analyses indicated that higher order attention processes were severely affected by TBI [F_{(2, 77)} = 5.66, p = 0.0051). Meta-regression analyses revealed significant improvement in visual attention deficit with time [p(mild) = 0.031, p(moderate-to-severe) = 0.002, p(severe) < 0.0001]. Taken together, these results demonstrate that visual attention is affected by TBI and that regular assessment of visual attention, using a systematic attention allocation task, may provide a useful clinical measure of cognitive impairment and change after TBI.

Investigating the relationship between users' eye movements and perceived product attributes in design concept evaluation

Eye movements as the indicators of human information processing have been studied in many domains. However, it is not clear how users' eye movements differ among specific product attribute, while visual impression of a product plays a crucial part in distinguishing product designs. Therefore, this paper attempts to establish guidance for exploring eye tracking applications in design concept validations through two case studies. The first case study investigated the product attributes based on the theory of cognitive-affective emotions. The second investigated the product attributes for apparent functionality and affective quality. The eye movements of 105 participants were analyzed when they evaluated the products images. The results indicated that product attributes perceived in evaluation tasks can be predicted from eye movements. Moreover, compared to the new users, experienced users had a longer mean fixation duration and tended to form their impressions of the product from multiple components.

Teleoperation of Highly Automated Vehicles in Public Transport: User-Centered Design of a Human-Machine Interface for Remote-Operation and Its Expert Usability Evaluation

Paving the way to future mobility, teleoperation of vehicles promises a reachable solution to effectively use the benefits of automated driving as long as fully automated vehicles (SAE 5) are not entirely feasible. Safety and reliability are assured by a human operator who remotely observes the vehicle and takes over control in cases of disturbances that exceed the vehicle automation’s skills. In order to integrate the vehicle’s automation and human remote-operation, we developed a novel user-centered human-machine interface (HMI) for teleoperation. It is tailored to the remote-operation of a highly automated shuttle (SAE 4) by a public transport control center and based on a systematic analysis of scenarios, of which detailed requirements were derived. Subsequently, a paper-pencil prototype was generated and refined until a click-dummy emerged. This click-dummy was evaluated by twelve control center professionals. The experts were presented the prototype in regular mode and were then asked to solve three scenarios with disturbances in the system. Using structured interview and questionnaire methodology, the prototype was evaluated regarding its usability, situation awareness, acceptance, and perceived workload. Results support our HMI design for teleoperation of a highly automated shuttle, especially regarding usability, acceptance, and workload. Participant ratings and comments indicated particularly high satisfaction with the interaction design to resolve disturbances and the presentation of camera images. Participants’ feedbacks provide valuable information for a refined HMI design as well as for further research.

The impact of predictability on dual-task performance and implications for resource-sharing accounts

The aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks.

Effect of highway directional signs on driver mental workload and behavior using eye movement and brain wave

The rapid development of expressways has led to an increasing number of place names that must be displayed on road guide signs. As a result, multi-board guide signs have been increasingly set up on expressways. The main aim of this study was to analyze the effect of the directional road sign displayed on multi and single-board signs on driver mental workload and behavior. 32 participants including 16 females (mean age = 24.7 years, standard deviation = 1.9 years) participated in the experiment and completed 3 driving simulation scenes. The setting of each scene-sign board was different: 1 board, 2 boards, and 3 boards. The driver needed to reach the designated destination according to the guidance of the road signs. Eye tracker was used to measure the fixation, saccade and electroencephalogram (EEG) was used to measure the alpha (8-13 hz) band absolute power in different signage scenarios. There are two major findings of the study. First, when the number of place names is less than or equal to 7, the multi-board sign generates more mental workload than the single-board sign does. The alpha band power of the driver's frontal area under the multiple boards is lower and affects driving performance (the deceleration is greater). Second, when the number of place names is more than 7, there is no significant difference in the effect on mental workload whether multi or single-board sign is used. However, compared to the single-board sign, drivers in the case of multi-board sign are likely to reduce the fixation duration and increase the number of saccades. The results suggest that it is not necessary to use multi-board signs when the number of place names is less than 7. These findings provide more safety considerations for the setting of multi-board guide signs in the future.

Driving impairments and duration of distractions: Assessing crash risk by harnessing microscopic naturalistic driving data

Distracted and impaired driving is a key contributing factor in crashes, leading to about 35% of all transportation-related deaths in recent years. Along these lines, cognitive issues like inattentiveness can further increase the chances of crash involvement. Despite its prevalence and importance, little is known about how the duration of these distractions is associated with critical events, such as crashes or near-crashes. With new sensors and increasing computational resources, it is possible to monitor drivers, vehicle performance, and roadway features to extract useful information, e.g., eyes off the road, indicating distraction and inattention. Using high-resolution microscopic SHRP2 naturalistic driving data, this study conducts in-depth analysis of both impairments and distractions. The data has more than 2 million seconds of observations in 7394 baselines (no event), 1228 near-crashes, and 617 crashes. The event data was processed and linked with driver behavior and roadway factors. The intervals of distracted driving during the period of observation (15 seconds) were extracted; next, rigorous fixed and random parameter logistic regression models of crash/near-crash risk were estimated. The results reveal that alcohol and drug impairment is associated with a substantial increase in crash/near-crash event involvement of 34%, and the highest correlations with crash risk include duration of distraction through dialing on a cellphone, texting while driving, and reaching for an object. Using detailed pre-crash data from instrumented vehicles, the study contributes by quantifying crash risk vis-à-vis detailed driving impairment and information on secondary task involvement, and discusses the implications of the results.

Differential Effects of Concurrent Tasks on Gait in Typically Developing Children: A Meta-Analysis

The objective of this study was to systematically analyze the literature surrounding dual-task (DT) effects on gait in typically developing children (TDC) and to conduct meta-analyses where applicable. After reviewing the abstracts of 676 articles, a total of 22 studies were included. The outcomes of interest were relative change in gait speed, cadence, stride length, double support time, variability in stride length between single and DT walking; and the exposures were concurrent tasks used for DT gait assessment. DT significantly affected each gait parameter (point estimate (PE), ranged from PE, -0.10; 95% CI, -0.13 to -0.08; p < .001 to PE, -0.66; 95% CI, -0.94 to -0.38; p < .001). The strength of DT effects varied by the concurrent task used. The greatest DT effect on gait speed, which was the most commonly presented outcome, was reported when upper extremity complex functional tasks (PE, -0.36; 95% CI, -0.49 to -0.23; p < .001, fine motor tasks (PE, -0.35; 95% CI, -0.38 to -0.32; p < .001), and verbal fluency tasks (PE, -0.26; 95% CI, -0.30 to -0.21; p < .001) were completed concurrently with gait. Children and adolescents experience performance decrements when they walk under DT conditions. Concurrent tasks differentially affect the degree of DT interference for each gait parameter.

Analysis and Evaluation of Eye Behavior for Marine Operation Training - A Pilot Study

This paper presents a new analysis approach for evaluating situation awareness in marine operation training. Taking advantage of eye tracking technology, the situation awareness reflected by visual attention can be visualized and analyzed. A scanpath similarity comparison method that allows group-wise comparisons is proposed. The term 'Expert zone' is introduced to evaluate the performance of novice operator based on expert operators' eye movement. It is used to evaluate performance of novice operators in groups in certain segment of marine operation. A pilot study of crane lifting experiment was carried out. Two target stages of operation for the load descending until total immersion to the seabed were selected and analyzed for both novice and expert operators. The group-wise evaluation method is proven to be able to access the performance of the operator. Besides that, from data analysis of fixation-related source and scanpath, the similarities and dissimilarities of eye behavior between novice and expert is concluded with the scanpath mode in target segment.

Estimating Pilots' Cognitive Load From Ocular Parameters Through Simulation and In-Flight Studies

Eye tracking is the process of measuring either the point of gaze (where one is looking) or the motion of an eye relative to the head. This paper investigated use of eye gaze trackers in military aviation environment to automatically estimate pilot’s cognitive load from ocular parameters. In the first study, we used a fixed base variable stability flight simulator with longitudinal tracking task and collected data from 14 military pilots. In a second study, we undertook four test flights with BAES Hawk Trainer and Jaguar aircrafts doing air to ground attack training missions and constant G level turn maneuvers up to +5G. Our study found that ocular parameters like rate of fixation is significantly different in different flying conditions. It also significantly correlated with rate of descent during air to ground dive training task, normal load factor (G) of the aircraft during constant G level turn maneuvers and pilot’s control inceptor and tracking error in simulation tasks. Results from our studies can be used for real time estimation of pilots’ cognitive load, providing suitable warnings and alerts to the pilot in cockpit and training of military pilots on cognitive load management during operational missions.

Training visual attention in a naturalistic visual environment

The efficiency of training visual attention in the central and peripheral visual field was investigated by means of a visual detection task that was performed in a naturalistic visual environment including numerous, time-varying visual distractors. We investigated the minimum number of repetitions of the training required to obtain the top performance and whether intra-day training improved performance as efficiently as inter-day training. Additionally, our research aimed to find out whether exposure to a demanding task such as a microsurgical intervention may cancel out the effects of training. Results showed that performance in visual attention peaked within three (for tasks in the central visual field) to seven (for tasks in the periphery) days subsequent to training. Intra-day training had no significant effect on performance. When attention training was administered after exposure to stress, improvement of attentional performance was more pronounced than when training was completed before the exposure. Our findings support the implementation of training in situ at work for more efficient results. Practitioner Summary: Visual attention is important in an increasing number of workplaces, such as with surveillance, inspection, or driving. This study shows that it is possible to train visual attention efficiently within three to seven days. Because our study was executed in a naturalistic environment, training results are more likely to reflect the effects in the real workplace.

Supervisors' Visual Attention Allocation Modeling Using Hybrid Entropy

With the improvement in automation technology, humans have now become supervisors of the complicated control systems that monitor the informative human–machine interface. Analyzing the visual attention allocation behaviors of supervisors is essential for the design and evaluation of the interface. Supervisors tend to pay attention to visual sections with information with more fuzziness, which makes themselves have a higher mental entropy. Supervisors tend to focus on the important information in the interface. In this paper, the fuzziness tendency is described by the probability of correct evaluation of the visual sections using hybrid entropy. The importance tendency is defined by the proposed value priority function. The function is based on the definition of the amount of information using the membership degrees of the importance. By combining these two cognitive tendencies, the informative top-down visual attention allocation mechanism was revealed, and the supervisors’ visual attention allocation model was built. The Building Automatic System (BAS) was used to monitor the environmental equipment in a subway, which is a typical informative human–machine interface. An experiment using the BAS simulator was conducted to verify the model. The results showed that the supervisor’s attention behavior was in good agreement with the proposed model. The effectiveness and comparison with the current models were also discussed. The proposed attention allocation model is effective and reasonable, which is promising for use in behavior analysis, cognitive optimization, and industrial design.

Assessing Dynamic Value for Safety Gear During a Rock Climbing Task

Value is a component of the SEEV model of attention combined with measures of salience, effort, and expectancy to characterize areas of interest in a visual workspace. In the current project, an assessment of dynamic value was created by prompting rock climbers to assess their post-hoc priority for placing safety gear at various points during a climb when the risk of injury from a fall varied. Analyses determined that, for expert and non-expert rock climbers, gear placement priority rose as time since the most recent gear placement increased, after controlling for climbing speed. Prediction of the attentional value of a target via dynamic estimates may be applied in other highly dynamic environments.

Are longer advertising slogans more dangerous? The influence of the length of ad slogans on drivers’ attention and motor behavior

The purpose of this project was to verify whether slogans displayed on roadside advertisements created a distraction for drivers. In order to explain the mechanisms underlying this phenomenon, Study 1 examined the impact of slogan length on attentional processing efficiency. Study 2 investigated the relationship between the length of the slogan and the motor behavior of respondents driving a car simulator. We assumed that slogan length would decrease the drivers’ task performance in both studies. Study 1 was conducted on a group of 70 participants, who completed a modified version of the Attention Network Test (ANT; Fan et al. Journal of Cognitive Neuroscience, 14(3), 340–347, 2002). The task consisted of visual ads intended to distract respondents from the primary task. Reaction times were significantly longer when ads had longer slogans compared to shorter slogans. Study 2, involving a car simulator, was conducted on a group of 53 drivers performing a task of driving in a convoy. Participants were shown billboards with ads at the roadside in random order (two pairs of corresponding ads with short and long text on it). Participants’ driving performance decreased when longer slogans were presented in comparison to the short-slogan condition. In conclusion, we interpret the results of Study 1 to indicate that longer slogan leads to a greater load of attentional processing. This subsequently leads to a reduction of the processing efficiency within attentional systems and further increases the amount of time to resist the irrelevant stimulus. A consequence of this, as shown in Study 2 using a car simulator, is a decrease in cognitive resources necessary for safe driving and therefore worse performance on a driving task.

Automation trust and attention allocation in multitasking workspace

Previous research suggests that operators with high workload can distrust and then poorly monitor automation, which has been generally inferred from automation dependence behaviors. To test automation monitoring more directly, the current study measured operators' visual attention allocation, workload, and trust toward imperfect automation in a dynamic multitasking environment. Participants concurrently performed a manual tracking task with two levels of difficulty and a system monitoring task assisted by an unreliable signaling system. Eye movement data indicate that operators allocate less visual attention to monitor automation when the tracking task is more difficult. Participants reported reduced levels of trust toward the signaling system when the tracking task demanded more focused visual attention. Analyses revealed that trust mediated the relationship between the load of the tracking task and attention allocation in Experiment 1, an effect that was not replicated in Experiment 2. Results imply a complex process underlying task load, visual attention allocation, and automation trust during multitasking. Automation designers should consider operators' task load in multitasking workspaces to avoid reduced automation monitoring and distrust toward imperfect signaling systems.

The effect of navigation display clutter on performance and attention allocation in presentation- and simulator-based driving experiments

Display clutter can have differential effects based on environmental factors, such as workload, stress, and experiment paradigm. The objectives of the current study were to assess the effects of display clutter on driver performance and attention allocation and compare results across two experimental paradigms. Forty-two participants searched high- and low-clutter in-car navigation displays for routine information either during a static, presentation-based experiment or in a dynamic, driving simulator experiment. Results revealed display clutter to significantly alter attention allocation and degrade performance in the presentation experiment, but had little to no effect on driver performance or attention allocation in the driving simulator experiment. Results suggest that display clutter may have its greatest effect on performance and attention allocation in domains requiring extended attention to the cluttered display compared to tasks in which the cluttered display acts as a support tool for secondary tasks.

Tracking and discrete dual task performance for different visual spatial stimulus-response mappings with focal and ambient vision

The effect of spatial compatibility for various display-control configurations on human performance was studied with a dual-task paradigm using a tracking task and a discrete response task. Degradation of performance on both tasks within the visual modality was observed and was considered to be most likely due to resource competition resulting from simultaneous task operation. It was found that the more complicated the mapping for the discrete spatial compatibility response task, the more severe the interference with the tracking task. Although performance on both the tracking and spatial response tasks was impaired, the magnitude of impairment was not as great as expected, implying that focal and ambient vision required for the tracking task and spatial task, respectively, might be deployed, at least partly, from separate resources. Participants here seemed to successfully use focal vision for tracking and ambient vision for identifying signal lights concurrently, reducing the expected keen competition for visual resources.

Glass half-full: On-road glance metrics differentiate crashes from near-crashes in the 100-Car data

BACKGROUND

Much of the driver distraction and inattention work to date has focused on concerns over drivers removing their eyes from the forward roadway to perform non-driving-related tasks, and its demonstrable link to safety consequences when these glances are timed at inopportune moments. This extensive literature has established, through the analyses of glance from naturalistic datasets, a clear relationship between eyes-off-road, lead vehicle closing kinematics, and near-crash/crash involvement.

OBJECTIVE

This paper looks at the role of driver expectation in influencing drivers' decisions about when and for how long to remove their eyes from the forward roadway in an analysis that consider the combined role of on- and off-road glances.

METHOD

Using glance data collected in the 100-Car Naturalistic Driving Study (NDS), near-crashes were examined separately from crashes to examine how momentary differences in glance allocation over the 25-s prior to a precipitating event can differentiate between these two distinct outcomes. Individual glance metrics of mean single glance duration (MSGD), total glance time (TGT), and glance count for off-road and on-road glance locations were analyzed. Output from the AttenD algorithm (Kircher and Ahlström, 2009) was also analyzed as a hybrid measure; in threading together on- and off-road glances over time, its output produces a pattern of glance behavior meaningful for examining attentional effects.

RESULTS

Individual glance metrics calculated at the epoch-level and binned by 10-s units of time across the available epoch lengths revealed that drivers in near-crashes have significantly longer on-road glances, and look less frequently between on- and off- road locations in the moments preceding a precipitating event as compared to crashes. During on-road glances, drivers in near-crashes were found to more frequently sample peripheral regions of the roadway than drivers in crashes. Output from the AttenD algorithm affirmed the cumulative net benefit of longer on-road glances and of improved attention management between on- and off-road locations.

CONCLUSION

The finding of longer on-road glances differentiating between safety-critical outcomes in the 100-Car NDS data underscores the importance of attention management in how drivers look both on and off the road. It is in the pattern of glances to and from the forward roadway that drivers obtained critical information necessary to inform their expectation of hazard potential to avoid a crash.

APPLICATION

This work may have important implications for attention management in the context of the increasing prevalence of in-vehicle demands as well as of vehicle automation.

A Closed-Loop Model of Operator Visual Attention, Situation Awareness, and Performance Across Automation Mode Transitions

OBJECTIVE

This article describes a closed-loop, integrated human-vehicle model designed to help understand the underlying cognitive processes that influenced changes in subject visual attention, mental workload, and situation awareness across control mode transitions in a simulated human-in-the-loop lunar landing experiment.

BACKGROUND

Control mode transitions from autopilot to manual flight may cause total attentional demands to exceed operator capacity. Attentional resources must be reallocated and reprioritized, which can increase the average uncertainty in the operator's estimates of low-priority system states. We define this increase in uncertainty as a reduction in situation awareness.

METHOD

We present a model built upon the optimal control model for state estimation, the crossover model for manual control, and the SEEV (salience, effort, expectancy, value) model for visual attention. We modify the SEEV attention executive to direct visual attention based, in part, on the uncertainty in the operator's estimates of system states.

RESULTS

The model was validated using the simulated lunar landing experimental data, demonstrating an average difference in the percentage of attention ≤3.6% for all simulator instruments. The model's predictions of mental workload and situation awareness, measured by task performance and system state uncertainty, also mimicked the experimental data.

CONCLUSION

Our model supports the hypothesis that visual attention is influenced by the uncertainty in system state estimates.

APPLICATION

Conceptualizing situation awareness around the metric of system state uncertainty is a valuable way for system designers to understand and predict how reallocations in the operator's visual attention during control mode transitions can produce reallocations in situation awareness of certain states.

Eye Tracking in Anesthesiology

Eye tracking has become a valuable method to study performance and cognition in diverse settings. For the present paper, we reviewed the literature on eye tracking in anesthesiology and identified nine publications. We have summarized the method and results of these publications. Further, we identified and discussed several methodological issues that occur when conducting eye tracking in anesthesiology, such as sample size, large data loss, and differences in study settings. Finally, we suggest future research topics in anesthesiology, which may particularly benefit from eye tracking.

Modeling of Situation Awareness Supported by Advanced Flight Deck Displays

A two module computational model of situation awareness is presented. One module, characterizing stage 1 (noticing) SA is based on the SEEV model of selective attention in complex environments, and consists of components of Salience (capturing attention), Effort (inhibiting attention movement), Expectancy (for events along a channel) and Value (of attending those events). These are combined additively, and accurately predict visual scanning on the flight deck and in driving. The second module characterizing stage 2 (understanding) SA, results from the integration of noticed information, and its decay if unattended. We describe briefly the application and validation of the attention module to pilot scanning of the synthetic vision system display suite in aviation, and in more detail, the application to predicting differences in situation awareness supported by three formats of a wake vortex display, designed to alert aircraft pilots to dangers in the flight path ahead.

Auditory Preemption versus Multiple Resources: Who Wins in Interruption Management?

We examined the effects of modality (auditory versus visual) and spatial separation when a simulated vehicle control (tracking) task (the ongoing task: OT) was time shared with a digit entry task (the interrupting task: IT), contrasting the predictions of auditory preemption theory with that of multiple resource theory. Participants performed the tracking task with auditory display of the phone numbers, or with visual display at eccentricities ranging from 0 deg (overlay) to 45 deg. Auditory input improved IT performance relative to visual, but disrupted OT performance, thereby supporting the role of auditory preemption. This cost did not grow with longer messages. In contrast, at eccentricities above 15 deg, auditory superiority emerged for both tasks, highlighting the role of multiple resources, and separation produced greater costs to the OT than to the IT. Therefore, both discrete tasks, and auditory delivery have inherent preemptive effects on the continuous visual OT. The results are also interpreted in the context of the non-linear costs to dual task performance with increasing separation from the eye-field to the headfield, and the support for different visual hemi-fields for concurrent processing of verbal and ambient spatial information.

Human Performance Models of Pilot Behavior

Five modeling teams from industry and academia were chosen by the NASA Aviation Safety and Security Program to develop human performance models (HPM) of pilots performing taxi operations and runway instrument approaches with and without advanced displays. One representative from each team will serve as a panelist to discuss their team's model architecture, augmentations and advancements to HPMs, and aviation-safety related lessons learned. Panelists will discuss how modeling results are influenced by a model's architecture and structure, the role of the external environment, specific modeling advances and future directions and challenges for human performance modeling in aviation.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching

OBJECTIVE

The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible.

BACKGROUND

The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed.

METHOD

In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker.

RESULTS

Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation.

CONCLUSIONS

The multiattribute decision model provided a good fit to the data.

APPLICATIONS

The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive.

Efficient multitasking: parallel versus serial processing of multiple tasks

In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling.

Calibration of skill and judgment in driving: development of a conceptual framework and the implications for road safety

Humans often make inflated or erroneous estimates of their own ability or performance. Such errors in calibration can be due to incomplete processing, neglect of available information or due to improper weighing or integration of the information and can impact our decision-making, risk tolerance, and behaviors. In the driving context, these outcomes can have important implications for safety. The current paper discusses the notion of calibration in the context of self-appraisals and self-competence as well as in models of self-regulation in driving. We further develop a conceptual framework for calibration in the driving context borrowing from earlier models of momentary demand regulation, information processing, and lens models for information selection and utilization. Finally, using the model we describe the implications for calibration (or, more specifically, errors in calibration) for our understanding of driver distraction, in-vehicle automation and autonomous vehicles, and the training of novice and inexperienced drivers.

A multinomial choice model approach for dynamic driver vision transitions

Exploring the continual process of drivers allocating their attention under varying conditions could be vital for preventing motor vehicle crashes. This study aims to model visual behaviors and to estimate the effects of various contributing factors on driver's vision transitions. A visual attention allocation framework, based on certain contributing attributes related to driving tasks and environmental conditions, has been developed. The associated logit type models for determining driver choices for focal points were successfully formulated and estimated by using naturalistic glance data from the 100-car event database. The results offer insights into driver visual behavior and patterns of visual attention allocation. The three focal points that drivers most frequently rely on and glance at are the forward, left and rear view mirror. The sample drivers were less likely to demonstrate troublesome transition patterns, particularly in mentally demanding situations. Additionally, instead of shifting vision directly between two non-forward focal points, the sample drivers frequently had an intermediate forward glance. Thus, seemingly unrelated paths could be grouped into explanatory patterns of driver attention allocation. Finally, in addition to the vision-transition patterns, the potential pitfalls of such patterns and possible countermeasures to improving safety are illustrated, focusing on situations when drivers are distracted, traveling at high speeds and approaching intersections.

Using Empirical Research and Computational Modeling to Predict Operator Response to Unexpected Events

This paper describes an effort to model and predict astronaut performance during sudden workload transitions in long duration missions. Our approach to the work is heavily based on empirical research. We have performed a set of meta-analyses 1) to identify the quantitative effects of poor sleep on task accuracy and task completion time, and 2) to develop a model of operator task selection during multitasking. We are currently developing a model, based on a literature review, to predict the effects of automation design factors on operator task performance. This paper gives an overview of the project, presents the overall model of operator performance during a workload transition, and describes the empirical and theoretical underpinnings of a model that predicts the effects of automation design on operator performance.