Engineering Psychology and Cognitive Ergonomics

Fitts’ law states that movement time can be predicted by knowing the size of a target to which a person is intending to move and the distance to be moved. The current study measured choice-movement time with three input devices commonly used in human-computer interaction tasks: response panel, computer mouse, and touch-screen. We also examined how direction of movement with the different input devices influences performance. Movement time was shorter when responses were made with the response panel than with the mouse and touch-screen. Furthermore, horizontal movement time was faster than vertical movement time, even when the size of the stimuli and distance to be moved were equal. Fitts’ law was used to estimate the slope and intercepts of the functions for each input device and dimension to determine whether the devices and dimensions had greater influence on the starting time or the speed of execution.

Auditory spatial cue accuracy and target uncertainty were examined within visual search. Participants identified a visual target to be present or absent under various target percentage conditions (25%, 50%, & 100%) with either an auditory cue which was spatially coincident with or displaced 4° or 8° (vertical or horizontal) from the target, or both an auditory and visual cue (circle 6.5° radius; identifying the local-target-area surrounding the target). Within the auditory cue condition, horizontal displacement was a greater detriment to target present search times than vertical displacement, regardless of error magnitude or target percentage. When provided an audiovisual cue, search times decreased 25% for present targets, and as much as 300% for absent targets. Furthermore, within audiovisual cue condition, while present target search times decreased with target percentage, absent target search times increased with target percentage. Cue condition and target uncertainty driven search strategies are discussed, with recommended design requirements and research implementations.

Metaphors based on perceptual similarity play a key role in stimulating creativity. Here, we present a metaphor interpretation tool using features of source and target to generate perceptual metaphors which might be conceptually very different, thereby generating new interpretations from familiar concepts.

The current work sets out to enhance our knowledge of changes or lack of changes in the speech signal when people are being deceptive. In particular, the study attempted to investigate the appropriateness of using speech cues in detecting deception. Truthful, deceptive and control speech was elicited from five speakers during an interview setting. The data was subjected to acoustic analysis and results are presented on a range of speech parameters including fundamental frequency (f0), overall intensity and mean vowel formants F1, F2 and F3. A significant correlation could not be established for any of the acoustic features examined. Directions for future work are highlighted.

High dynamic range (HDR) color images are evaluated for Kansei impression by two groups of observers: Japanese and Chinese. Twenty HDR images were created by converting each of five HDR images with different tone curve properties into four screen sizes. As a result, the subjective rating value for the psychophysical properties of images, such as “Light” and “Dark,” increased or decreased monotonically with the average brightness

L*

, but not with image size. On the other hand, the rating value for some Kansei evaluations, including “Natural” and “Clear,” followed the same patterns. Next, we applied factor analysis to the results, having divided the data into Japanese and Chinese. The analysis result indicated that two and three factors were extracted from the rating value evaluated by Chinese and Japanese participants, respectively. These results suggest that Japanese observers evaluated HDR images in more detail than Chinese ones did.

In this paper, we propose a personalized emotional prediction method using the user’s explicit emotion. The proposed method predicts the user’s emotion based on Thayer’s 2-dimensional emotion model, which consists of arousal and valence. We construct a user-object dataset using a self-assessment manikin about IAPS photographs, and predict the target user’s arousal and valence by collaborative filtering. To evaluate performance of the proposed method, we divide the user-object dataset into a test set and training set, and then observe the difference between real emotion and predicted emotion in the 2-dimensional emotion model. As a result, we confirm that the proposed method is effective for predicting the user’s emotion.

The LED (light emitting diode, also referred to as LED) have already been used widely. However, despite the high visibility of LED with high brightness performance, it also leads to a glare problem, which generates a direct security issue in applying to traffics. Therefore, this research aimed to study how to make the LED display sign be more legible under high illuminative environments and to avoid the observers feeling dazzling glare under low illuminative environments. This research firstly studied the literatures to explore the drivers of visual ergonomic as well as the optical properties of LED, and investigated the relatively existing norms for engineering vehicle LED display signs. Three variables were set in this study: three kinds of ambient illumination, four kinds of luminance contrast and two kinds of character form. In the first phase of the experiment, subjects observed LED display signs in both near and distant locations and filled out the SWN scale (Subjective Well-being under Neuroleptics), and in the second phase, subjects were then asked to moved forward and recorded their perceptions of comfort and glare to distance range. The findings demonstrated that, there was no variation in subjective evaluation to display signs with no backgrounds either in the near or distant locations, while to display signs with backgrounds, the subjects perceptions were the farther the distance, the clearer the legibility; higher ambient illumination could effectively reduce observers of glare perception to LED display signs; display signs with backgrounds at the luminance contrast of 3:1 (L max = 3100, L min = 1033 cd / m

2

) showed the lowest uncomfortable and glare level to observers. The two forms of character showed no significant variation in affecting observers in terms of the comfort and glare perception.

In previous research we have investigated the effect of screen size on the perceptual mental rotation task (MRT) by comparing performance on a large 230 inches display with that on a standard 14.1 inches laptop display. The former work indicated that females might gain an advantage over males on a larger display. The current study confirms a significant female advantage over male performance in the MRT. However, our current findings helped to reveal that, instead of improving the females’ performance, the screen size had a detrimental effect on male performance, while female performance actually remained unaffected by both the large object size than the standard one.

Designing systems for the special interests and needs of older user has become an important subject. However, necessary usability evaluations are time and resource consuming. One way of automation lies in simulating UI use. Since substantial sensory and cognitive age-related effects on the human visual system have been observed, mechanisms of

Visual Attention (VA)

are promising candidates for simulating GUI interactions specific for older users. This article discusses VA mechanisms relevant for simulating age-related effects in GUI interactions. An integration of such mechanisms is discussed on basis of the MeMo workbench, a rule-based approach that uses UI interaction simulations for uncovering usability problems. In the end, simulation of GUI interactions cannot replace human-based usability evaluation, but can provide early feedback for GUI designs, reducing time and resource demands for evaluations. In that, VA provides an instrumental framework for considering age-related effects in simulations of GUI interactions by older users.

In an aged society, easy-to-use information devices are necessary. In order to develop information devices which elderly adults can use easily, it is important to bring out characteristics of elderly adults in using information devices based on their cognitive functions. In this study, the authors focus on a relation between memory function and exploration behavior in a hierarchical menu while learning process. An experiment is conducted with eight elderly adults and eight young adults. In this experiment, a hierarchical menu composed based on the library classification, not actual hierarchical menus, is used in order to eliminate differences of knowledge about information devices between elderly and young adults. As a result, it seems that decrease of episodic memory increases a possibility of improper selections in the hierarchical menu when doing the same operations as previous operations.

This study compares the performances of paper and electronic media during a reading task that includes frequent page turning. In the experiment, 18 subjects read multi-page documents aloud while referring to endnotes using paper, a large display, and a small display. Results revealed that reading from paper was 6.8% faster than reading from a large electronic display and 11.4% faster than reading from a small electronic display. No difference was found between scores of recognition tests of important words of documents among the three conditions, which indicates that paper is the most effective medium for people to read text speedily without reducing comprehension. Detailed analyses of the reading process show that, in the Paper condition, people perform both text reading and page-turning simultaneously. However, when using computer displays, reading and turning pages were divided completely and performed separately.

Mobile devices offer an advantageous platform on which to perform training simulations. However, they create new issues that are unique to mobile device development. First we will explore several reasons for using mobile devices for training simulators, instead of desktop or legacy-based systems. Once we have established the requirements of mobile simulators, we will discern some of the differences that arise between major mobile platforms in each development area. Finally we propose a solution that will address these differences and aid developers in creating cross-platform mobile simulations.

We propose a new method in which scents are ejected through the display screen in the direction of a viewer in order to enhance the reality of the visual images. A thin LED display panel filled with tiny pores was made for this experiment, and an air control system using a blower was placed behind the screen. We proved that the direction of airflow was controlled and scents properly travelled through the pores to the front side of the screen. Moreover, the effectiveness to an advertising field of this system was estimated by simulating an actual situation in which various advertisements are around using the immersive VR System. The subjects’ eye movements and impressions, when they look at the scented advertisements while walking, were analyzed.

A widely-used method for entering texts with mobile phones is the multi-tapping one. To understand the internal processes of humans while doing multi-tapping, we designed an experiment with time pressure, that is, to multi-tap a key for the prescribed number of times as fast as possible. We observed three types in time series data for inter-tap intervals: Type I (Plan and Do), Type II (Do and Adjust), and Type III (Mixture of Type I and II). And, for the distribution of errors in the tapping, we found a subitizing-counting analogue. That is, if the instructed number of tapping was smaller (< 4), the error rate was smaller, and if the number was larger (> 4), the error rate rose abruptly. These findings could lead to the model of human cognition and manipulation of the number, hence to the design of the usable human interface.

Wolfe J M. et al found that subject’s miss rate increased markedly when target prevalence decreased in simulated X-ray luggage screening task, which was so-called the low prevalence effect. He thought it was caused by shift of observer’s decision criteria. But the number of trials with target (NTT) also affected the effect. The present study had two experiments, and there were two blocks in each experiment. Subjects in Exp 1 were in different NTT (20 vs. 100) but the same target prevalence (both 50%); In Exp 2, NTT was the same (both 20) but the target prevalence was different (50% vs. 5%). The results showed that subject’s miss rate was mainly changed with NTT, and decision criteria was up to the target prevalence, Wolfe’s conclusion was not completely correct.

This paper presents the method of detecting driver’s drowsiness level from facial expressions. Our method is executed according to the following flow: taking a driver’s facial image, tracing the facial features by image processing, and classifying the driver’s drowsiness level by pattern classification. We found that facial expression had the highest linear correlation with brain waves as the general index of drowsiness during monotonous driving. After analyzing the facial muscle activities, we determined 17 feature points on face for detecting driver drowsiness. A camera set on a dashboard recorded the driver’s facial image. We applied Active Appearance Model (AAM) for measuring the 3-dimensional coordinates of the feature points on the facial image. In order to classify drowsiness into 6 levels, we applied k-Nearest-Neighbor method. As a result, the average Root Mean Square Errors (RMSE) among 13 participants was less than 1.0 level. Our method also detected the driver’s smile.

Driver’s fatigue has been verified as a major factor in many traffic accidents. The estimation of driver’s vigilance by steering wheel angle is good way because it is a non-invasive method compared with EEG. An adaptive vigilance estimation methodology based on steering wheel angle information is proposed. The sample data classification index is built from EEG and PVT information of ten driver’s virtual driving experiment on driving simulator. According to the geometry information of road centerline and the location of the automobile center, a new algorithm is proposed to compute the lane deviation. The correlation coefficient between steering wheel angle and lane deviation are computed, and the results show that their correlation level is 0.05. Based on the steering wheel angle, the driver fatigue evaluation model is established by the Bayesian Network (BN). The structure and parameters for BN model are determined after adaptive training. The experiment results verified that this model is effective to identify driver’s fatigue level.

In the recent aged society, the framework for assisting safe driving should be prepared with understanding the elderly driver’s driving performance and their psychological features. The purpose of this study is aimed to obtain the fundamental data of aged driver for their effective assist-system. First, using driving simulator, aged people were observed their driving behaviors in various conditions at intersections compared with young drivers. These behaviors were measured in the condition of right and left turns and crossing. As the results, in particular, significantly slower approaches were observed on every occasion, and the unstable driving behaviors were examined. Next, on the field tests of real running in proving ground, the aged drivers were apt to run rapidly in the case of approaching the crossing compared with young drivers. These driving performances should be interfered with the traffic flow and exposed to the risk of accidents.

This study investigates the influence of false and missing alarms of safety system on drivers’ risk-taking behavior by laboratory experiments. The task is to move a vehicle from below to top through an intersection displayed on a PC monitor without colliding with crossing traffic. Participants performed the task under different experimental conditions with different types of system failure: (1) no failure, (2) false alarm, (3) missing alarm, and (4) no information. We conducted two experiments. The difference between Experiment 1 (E1) and Experiment 2 (E2) is the frequency of false or missing alarms: erroneous alarms occurred twice as many in E2 as E1. The differences of the result between E1 and E2 indicate that the different frequencies of missing alarm have a different effect on risk-taking behavior.

The goal of our research is to develop a method to assess the arousal states using facial images of drivers. Multi-dimensional physiological indices are expected to be alternative external criteria of arousal states to manual coding of facial expression which require a lot of human resources. Changes in multi dimensional physiological indices (i.e., blink categories, skin conductance, EEG alpha wave, respiration, heart rate variability) depending on the arousal states defined by the combination of “arousal level” and the presence of “effort” to wake up were studied. Multiple linear regression analysis was also executed using one of the face scores (“arousal level” or “effort”) as dependent variables and the physiological indices as explanatory variables. Relatively high multiple correlation coefficients were obtained, however, the number and combination of selected indices showed great differences between individuals. To obtain common equations is an issue in future.

Driver distraction has become a major concern for transportation safety due to the increasing use of in–vehicle devices. To reduce safety risk, it is crucial to understand how fundamental aspects of distracting activities affect driver cognition in terms of roadway situation awareness. This study used a simulator-based experiment to investigate the effects of visual, cognitive and simultaneous distraction on operational and tactical control of vehicles. Twenty drivers participated in the study and drove in following or passing driving scenarios under four distraction conditions (without, with visual, with cognitive, and with simultaneous distraction). Results revealed visual distraction to affect all aspects of driver situation awareness. Cognitive distraction affected comprehension and projection of roadway and vehicle states. Correlation analyses revealed decrements in driver SA due to distraction to be associated with decreases in performance.

Poor or degraded situation awareness has previously been identified as a contributory factor in crashes at rail level crossings. Despite this, the concept remains largely unexplored in this context. This paper describes an exploratory on-road study focusing on novice and experienced driver situation awareness whilst negotiating rail level crossings. Participants drove a pre-determined urban route, incorporating two rail level crossings, in an instrumented vehicle. Situation awareness was assessed using propositional networks which were constructed based on content analyses of driver verbal protocols. Differences between drivers’ situation awareness were found in terms of the information underpinning it and the integration of this information. It is concluded that, whilst negotiating the two rail level crossings, inexperienced drivers had less efficient situation awareness than experienced drivers. In closing, the implications of this study are discussed along with a series of recommendations for further research in this context.

This paper investigates the influence of environmental factors and driver distraction on the eye-fixation-related potential (EFRP) of drivers. Brightness and traffic conditions were set up as environmental factors in experiments using a motion-based driving simulator, and several cognitive tasks were given simultaneously to the participants while they simulated driving. The results of this experiment show that brightness and traffic flow do not affect the EFRP. This shows that EFRP is a stable index of driver distraction.

Incompatibility between different types of road user is a problem that previous research has shown to be resistant to a range of interventions. Cars and motorcycles are particularly prone to this. Insight is provided in this paper by a naturalistic method using concurrent verbal protocols and an automatic, highly reliable semantic network creation tool. Analysis of the structure and content of the semantic networks reveals a greater degree of cognitive compatibility on faster roads such as motorways, but evidence of more critical incompatibilities on country roads and junctions. The results are discussed in terms of practical measures such as road signs which warn of events behind as well as in front, cross-mode training and the concept of route driveability.

The present study addressed age-related differences in performances and strategies developed by web users while searching for information. Ten older and 10 younger adults had to search for information with Google and to answer 9 questions varying in complexity: from simple ones (participants needed to use keywords provided in the questions) to impossible ones (no answer existed). The results showed that older participants had lower performances than younger ones; age-related differences were more particularly marked as the question complexity increased. Regression analyses showed that processing speed and cognitive flexibility accounted for a large part of the variance in performances. The younger and older participants also differed in the strategies they developed while searching for information. The older participants tended to focus on the evaluation of the results provided by Google. In contrast, the younger participants tended to plan and regulate their activity, this last strategy provided better performances.

Websites on e-commerce often display large amounts of multi-media and information, creating problems for viewers when locating specific information. This research uses the concepts of template and selective attention to understand the cognitive simplification in finding information and browsing websites. Utilizing content analysis with 240 university students as subjects, we conducted an experiment on information retention with browsing a shopping website. Although the amount of information displayed by the website was staggering, the result of the experiment showed that participants applied a template built up through past experiences of what’s important and where things belong. This internal map containing three mechanisms: segmentation, grouping and attention, is then used to create an efficient task strategy, to segment the page, and to categorize the information. This research tried to understand the attributes of template for users who are browsing Websites. The “findability” of online information would be improved if the arrangement of information of a web site were the same as what viewers expected.

This study investigated the accuracy and completeness of mental models users have of Web search engines in the context of a comparison of matched data obtained from samples from 2000 and 2010. The performance measures time, steps and accuracy were assessed along with 17 salient features of Web search engines identified in the study conducted in 2000. The results indicated that the 2010 sample had improved significantly across all performance measures. The two samples did, however, identify an equal number of salient features (N=7). It was clear from the detailed analyses of the salient features though, that that the accuracy and completeness of users’ mental models of search engines had demonstrably improved from 2000. So, while users’ mental models of Web search engines still remain largely inaccurate and incomplete, their alignment with designer’s conceptualisations has improved.

The development of Information and communication technology (ICT) has changed the action of business. The view to considered SEs sector as homogeneous, within which SEs take an ordered, sequential e-progression on the route to ICT adoption, and postulate that businesses move in stages from basic use of the Internet to the full integration of business systems and redesign of business processes. The aim of this paper is to conduct an analysis of the stage model in the context of the progression of ICT adoption by SEs. Empirical cases are given that show weaknesses of stage models to explain e-progression in SEs, the stage model are too general and do not take into account the diversity of SEs and focused upon factors such as firm size, age, owner/manager characteristics and geographical position This variety of different perspectives on the adoption of ICT by SEs suggests the need for a multidimensional framework to more adequate explained e-progression in SEs.

There are many factors that effect student learning and achievement. Factors such as socioeconomic status, class size, a child’s learning style, and parental involvement all have influence on a student’s achievement in school. In this study, we focus only on the factor of parental involvement as it relates to parent-teacher communication. Parent-teacher communication has traditionally been conducted through parent-teacher conferences, personal letters to parents, telephone calls home, etc. However, the growth of the Internet based communications such as e-mails and blogs have expanded the ways in which parent-teacher communication can occur. The objective of this study is to find out how blogs, a lightweight web 2.0 technology, are used to support communication between parents and teachers in different national culture settings. The findings of this interview study suggested that cultural values, privacy policies, teacher background and technology knowledge have influenced the use of blog in parent-teacher communication.

Social tagging as a new approach for metadata creation has emerged to support browsing, searching, sharing on social network sites. Tag clouds are visual displays of social tags. In this paper we reported a user study on tag cloud perception. The goal of our evaluation is to investigate the effect of some of the different properties that can be utilized in presenting tags e.g. tag font size, tag location. Both behavior data and eye tracking data demonstrated a significant effect of font size, but effect of tag locations was mixed. Big tags were recalled better than medium and small font tags regardless of their locations in a tag cloud. Tags in the middle circle of a tag cloud received longer eye duration than outer circle, but were not recalled better.

In tasks requiring dealing with variable situations, workers are expected to do more than following prescribed instructions. In this paper, we presented our view and framework for creating instructions with a good balance between the flexibility of abstract principles and the preciseness of concrete instances, which aims at helping instruction receivers become capable of dealing with variable situations where no concrete instructions are available. Our approach represents knowledge using an abstraction hierarchy. It is situated in our grand model which deals with the whole picture of knowledge communication. A case study is also presented, which suggests that seen in our view existing manuals can be improved by providing them with principles combined with instance-dependent variables.

Decision making is a critical part of design. Designers must constantly compare, weigh and select design options throughout the design process. The effectiveness of those decisions impacts the effectiveness of the final design. In this paper, we compare two decision support systems, one that allows designers to enter and visualize the uncertainty in each alternative, and one that does not. We compared differences in the designers’ perceptions of whether they had sufficient information to make a choice, and their confidence in their choice. The goal is

not

to make designers more confident of their decisions, but rather to help them evaluate realistically whether they have sufficient information to make a clear choice.

A big challenge of software test managers is the limited test time. Especially the system test, where the whole integrated software system is tested shortly before delivery to the customer, is affected by this limitation. During the system test usually several test cycles are needed. However, a test manager cannot execute all available test cases in each test cycle due to the limited test time. He/she has to decide which test cases have to be executed in each test cycle in order to find new possible faults of the software. In this paper the Adaptive Test Management System (ATMS) based on software agents is presented which relieves the test manager from this complex manual work by using software agents for prioritizing test cases based on current information about the software system, the test cases and the human factors of the developers. The goal of the ATMS is to maximize the number of found faults in the available test time with the determined prioritization order.

A novel approach to cognitive automation of assembly processes is introduced. An experimental assembly cell with two robots has been designed to proof the concept. The cell’s numerical control – termed a cognitive control unit (CCU) – is able to simulate human information processing at a rule-based level of cognitive control on the basis of the SOAR cognitive architecture. Thus the CCU can plan assembly processes autonomously and can react to changes in assembly processes due to increasing number of products that have to be assembled in a large variety in production space as well as changing or uncertain conditions. To develop a “Humanoid-Mode” for automated assembly systems similar to the H-metaphor for automated vehicles human assembly strategies where identified in empirical investigations and formulated as production rules. When the CCU is enriched with these production rules underlying human heuristics, a significant increase of the predictability of a robot when assembling products can be achieved.

We have previously advocated

adaptable

interaction with automation through approaches derived from human-human delegation and using the metaphor of a sports team’s “playbook”. In work sponsored by the U.S. Army’s Aeroflightdynamics Directorate (AFDD), we have been studying the effects of play-based delegation on human-machine system performance. Of particular interest is performance with plays in “non-optimal play environments” (NOPE) where no, or only poorly fitting, plays exist to achieve needed behaviors. Plays have been shown to offer benefits in situations for which they are customized, but more interesting is whether complacency, expectation, loss of training, and automation bias might affect performance when plays do not perfectly fit. We provide a taxonomy of NOPE conditions and report on the exploration of some of these conditions in a series of three experiments performed to date.

In the refining industry, control room and field operators document their daily activities using shift logs. These logs are supposed to be an important part of the shift handover process and are the mechanism by which activities are coordinated across shifts. Previous research identified the need for a more structured approach to shift handover. However, the value of a structured approach has never been demonstrated experimentally. We report here on an experiment sponsored by the Abnormal Situation Management Consortium conducted at the ENGEN Refinery that compared the quality of shift handovers using a structured checklist-integrated logbook to a more traditional less structured logging approach. The results showed that significant benefits to situation awareness derive from the more structured approach.

This article focuses on the experimental identification of changes in human behaviour patterns of UAV-operators guiding multiple UAVs from a helicopter cockpit. These changes are based on self-regulation mechanisms of the operators to adapt to the current task and workload demands. Main objective of the use of these so called self-adaptive strategies is to avoid overload situations, and to retard exceeding capacity limits, to maintain overall acceptable performance as long as possible. Expressed by shedding and deferring tasks of lesser importance, or the relaxation of self-imposed criteria, these strategies lead to an observable change of human behaviour patterns, prior to grave performance decrements. This article describes a laboratory experiment utilising a virtual flight simulator to stimulate operator’s workload and observe their mitigation strategies by means of gaze detection and a detailed interaction monitoring. Using the observed behaviour changes in an assistant system as indicator for high workload situations of the operator, it shall be possible to support the operator prior the occurrence of errors.

This work, a collaboration between Alstom Transport and the MIT Humans and Automation Laboratory (HAL), is focused on the development of an interactive in-cab scheduling interface for train operators. Currently, operators rely on a combination of paper schedules, paper speed charts, and rote memorization to meet the many demands of train operation. The separation of this information over multiple sources shifts driver attention away from the windscreen and may result in increased workload levels and safety compromises. A Hybrid Cognitive Task Analysis (hCTA), which derives the information requirements necessary to meet mission goals directly from operational tasks, was conducted to generate cognitive requirements for the desired scheduling display. The resulting seventeen requirements were used to guide the development of a new scheduling display, which is presented.

How to express fire spread efficiently and effectively to firefighters was an important issue. The present study aimed to investigate how to present the fire alarm information, focusing on whether natural language alarm presentation was better than the alarm list presentation. Objective method and subjective evaluation were used to compare the difference among different expressions. The results revealed that natural language was better than alarm list in described a fire spread situation, and the effect was more robust when spatial information was added. Traditional alarm list was more accuracy than other forms, but it cost more time to read and comprehension. So natural language with spatial information will be recommended to the future design of fire alarm system.

This paper describes the results and differences between students and professionals who used a GPS based GIS as a collaborative tool in an experimental emergency response study. A total of 132 students, forming 22 groups and 108 professionals forming 18 groups were tested. Differences in both performance and behaviors between the groups have been identified. In the discussion we reflect on the importance to be aware of the participants’ background and behaviors while selecting the participants in an experimental study.

There is widespread agreement among scholars and practitioners that terrorism scholarship suffers from a lack of primary-source field research [1]. The absence of solid ethnographic research has yielded studies that suffer from a lack of rigorous analysis and often result in opinion masquerading as analysis. This dearth of field work stems in part from a failure to integrate ethnographic research into computational modeling efforts. The project outlined in this paper seeks to redress this deficiency by combining the strengths of ethnographic field research with sophisticated computational models of individual and group behavior. Specifically, we analyze data from interview transcripts, news reports, and other open sources concerning the militant activist group Al-Muhajiroun and the terrorist groups Provisional Irish Republican Army (PIRA) and Revolutionary Armed Forces of Colombia (FARC). Using

competitive adaptation

as a comparative organizational framework, this project focuses on the process by which adversaries learn from each other in complex adaptive systems and tailor their activities to achieve their organizational goals in light of their opponents’ action.

In a rapidly aged society, providing mobility aids such as motorized wheelchairs is becoming increasingly important. Such low-speed vehicles have recently been developed with autonomous locomotion capabilities. In order to enhance the security and safety offered by these vehicles, human-machine interfaces are needed to inform the rider about the path of locomotion that is being taken. In this research we developed a prototype steering interface that provides haptic information to the rider about the locomotion of the vehicle. Initial experiments using a powered wheelchair simulator were performed to study the most acceptable temporal characteristics of the system in terms of the timing of the information provided to the rider.

Evaluation of the design of complex automation and control room systems is an essential phase in the design process in the nuclear field. For example, in order to meet the nuclear regulatory requirements, the new control room systems have to be evaluated in full-scope simulators to achieve a validation of the systems. We have developed a specific approach for the pre-validation of human-system interfaces and applied the method to evaluate the control room designs of a Finnish nuclear power plant. Some lessons learned from previous tests are provided. The paper will also discuss some open questions concerning the use of pre-validation test data. One of the most interesting questions is how pre-validation test data can be used in the final validation of a system, and how a set of pre-validation tests can support the validation by providing cumulative evidence of the functionality and usability of the system.

This paper presents a study conducted for the Shades of Grey EPSRC research project (EP/H02302X/1), which aims to develop a suite of interventions for identifying terrorist activities. The study investigated the body movements demonstrated by participants while waiting to be interviewed, in one of two conditions: preparing to lie or preparing to tell the truth. The effect of self-awareness was also investigated, with half of the participants sitting in front of a full length mirror during the waiting period. The other half faced a blank wall. A significant interaction was found for the duration of hand/arm movements between the deception and self-awareness conditions (F=4.335, df=1;76, p<0.05). Without a mirror, participants expecting to lie spent less time moving their hands than those expecting to tell the truth; the opposite was seen in the presence of a mirror. This finding indicates a new research area worth further investigation.

In a simulated task of airport security inspection for threat items of knives, guns and IEDs, the difference between screeners and naïve people was analysed in terms of detection performance, attention allocation and workload. The detection performance of screeners was significantly better than that of naïve people. Compared to naïve observers, screeners concentrated on one or two potential threat items and ignored some irrelevant contents in the X-ray images which are showed by fixation maps. In order to understand how observers missed targets the workload between hit and miss decisions was compared. Unfortunately, there was no difference on workload when they hit or missed the targets where the dwell time on the targets of the hit decisions was longer than that of miss decisions. The findings may highlight how the search expertise is developed and provide information for improving training program.

In a human-in-the-loop simulation, a scheduler delivered aircraft to meter fixes in the Los Angeles terminal area with a -60 to +30 second accuracy. This study investigated whether, and how well, controllers could control aircraft to land them as close to their scheduled time of arrival (STA) as possible using speed control alone. Controllers were assigned one of three levels of tools to assist them but had to compensate for errors in the forecast winds that had not been taken into account by the scheduler. Results show that speed clearances were sufficient under all conditions to maneuver aircraft closer to their STAs. From participant reports, this form of control incurred manageable workload and two of the three levels of tools were deemed easy to use.

In two studies using variations of the Prisoner’s Dilemma game, we explore the combined impact of individual traits and social context on aggressive behavior. In the first study, we compared defection rates in the Iterated Prisoner’s Dilemma when participants were presented with a payoff matrix (Description condition) or learned payoffs through experience (Experience condition). Interpersonal trust and maximizing tendency led to relatively more cooperation in the Description condition than in the Experience condition, demonstrating that individual characteristics manifest differently depending on the information available to decision-makers. In the second study, we employed a new game paradigm, the Intergroup Prisoner’s Dilemma with Intragroup Power Dynamics, to examine the way that power motives influence extreme aggressive behavior. We discovered that certain individuals exhibit very high levels of defection, but only when they play with particular combinations of predefined strategies, suggesting further how the confluence of individual factors and context can induce aggression.

This paper reports the DScenT (Detecting Scent Trails) project, which brought together technologists and behavioural scientists to design and evaluate novel methods for countering terrorism in public places. Through a mixture of prototyping and empirical evaluations, we developed and assessed an immersive environment for detecting and investigating deceptive behaviours indicative of terrorist activities. The environment comprised a location-based game called Cutting Corners. The game was used in field trials to test the efficacy of different methods for collecting and using evidence during investigative interviews with mock terrorist suspects and to examine effects of play on attitudes towards surveillance and counter-terrorism.

Development of behavioral pattern recognition and analysis skills is an essential element of counter-terrorism training, particularly in the field. Three classes of behavioral measures were collected in an assessment of skill acquisition during a US Joint Forces Command (JFCOM)-sponsored course consisting of combat tracking and combat profiling segments. These included situational judgment tests, structured behavioral observation checklists, and qualitative assessments of the emergence of specific knowledge-skills-attitudes over the course of training. Evidence was present in all three types of measures to indicate that behavioral pattern recognition and analysis skills were successfully acquired by most students (a mix of Army and civilian law enforcement personnel). The paper describes both the types of skills acquired and the statistical evidence that supports their acquisition over the course of field training. Implications for broader training of these critical skills are also discussed.

The objective of the reported work was to study the use and applicability of applied cognitive ergonomics design principles for fighter aircraft, with examples from the modern Swedish swing-role aircraft Gripen. Methods used were a literature review of relevant design principles together with an analysis of their applicability to the fighter aircraft domain as well as interviews of developers and scrutinized system documentation of ongoing fighter aircraft development at Saab. As a result of those activities, we can here present a brief description of cognitive ergonomics design principles applied in the Gripen fighter aircraft, and the development process for human-machine interaction for fighter aircraft. Finally, considerations for the design process for fighter aircraft are discussed in the context of that description.

Extensive US Army programs are being pursued to increase the effectiveness of unmanned vehicles for diverse missions during future combat. The following paper identified 23 human-robot interaction (HRI) guidelines related to interface design, procedural issues, individual differences and training implications based on three HRI research programs. The programs range from simulation experiments that investigated robot control in a multitasking environment from a mounted combat vehicle, to reconnaissance missions in a miniature Iraqi city that focused on Soldier–robot teaming relationships, to field studies at Ft. Benning that examined interface design issues for Soldiers supervising or controlling small robots.

The aim of this project was to design and build a test-rig that is capable of analyzing small unmanned aerial vehicles (SUAV) co-axial rotor systems. The intention of the test-rig development was to highlight important aeromechanical components and variables that dictate the co-axial units flight performance, with the intention of optimizing the propulsion systems for use on HALO

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a co-axial SUAV designed by the Autonomous Systems Lab at Middlesex University. The major contributions of this paper are: an optimum COTS co-axial configuration with regards to motor and propeller variations, a thorough review and validation of co-axial rotor systems inter-rotor spacing which in turn identified an optimum H/D ratio region of between (0.41–0.65).

Trust in automation, and particularly maintaining an adequate level of trust in automation is now recognized as a major performance factor in supervisory control. Leveraging man-machine interaction is seen as a promising approach to influence the level of trust of an operator. Two problems need to be addressed in order to reach this goal: first measuring the level of trust; second acting on the level of trust to reach a more appropriate level. In this paper, we tackle the first problem, and propose to use a computational dialogue modelling approach to evaluate trust dynamically. We describe our model on two examples and give some perspectives.

Over the last twenty years, the emerging roles of unmanned aerial/ground vehicles in the U.S. military presented a number of different research opportunities in usability and training, ranging from robotic control interfaces to human-robot team collaboration. In this paper we present a testbed that we developed as a flexible software platform to explore a variety of training and coordination issues with UXVs for military application.

After action review (AAR) in the distributed setting provides for some unique problems. Some of these problems include remote facilitation of an after action review, keeping a lightweight infrastructure that can handle large amounts of throughput and allowing for different AAR sessions to be run simultaneously. This paper proposes a method for developing a facilitative infrastructure in the AAR setting while providing a solution that allows for syncing of multiple AAR software to one review session.

In this paper we discuss a conceptual framework that supports operational scenarios with multiple UAVs and operators. These UAVs possess different levels of autonomy while the operators have variable skill sets. The scenarios themselves encompass different missions, with different phases (requiring different levels of attention from the operator) and with the occurrence of various exogenous events. This framework was employed in the development of a Command and Control (C2) application which is capable of operator advisement, self adaptation, and automatic task distribution among operators and UAVs, depending on mission objectives, phase and occurrences. This C2 application enables a clear overview of the remote environment by placing the operator closer to the control loop, whether it is at an abstract or low level of control. Consequently there is an improvement of task redistribution and situation awareness, as well as reduction of workload.

Certified Flight Instructors (CFIs) in general aviation are tasked with training student pilots the knowledge and skills related to piloting an aircraft. This requires CFIs to have indepth knowledge about common student errors including early indicators of non-optimal performance in flight, an understanding of probable root cause(s) of non-optimal performance, and instructional techniques to address root cause(s). There is an opportunity to improve CFIs’ awareness of common student errors that lead to accidents/incidents and training effectiveness by integrating low fidelity scenario-based training. Such scenarios provided using low cost simulation environments coupled with detailed performance measures outlined in the ADAPT framework can aid CFIs in understanding common errors so that effective recognition and appropriate training intervention is provided to student pilots with the goal of optimizing training while minimizing student accidents/incidents.

Human error has been identified as the primary risk to flight safety. Two of the more pervasive aspects of Human Factors encountered throughout the airworthiness regulations are error and workload. However, as a result of increasing organizational inter-dependence and integration of aircraft systems it is argued that the manner in which these issues are addressed in the aviation regulations is becoming increasingly incompatible with human and organizational behavior in an airline. Workload and error are both products of complex interactions between equipment design, procedures, training and the environment. These issues cannot be regulated on a localized basis. A more systemic, holistic approach to Human Factors regulation is required. It is suggested that a Safety Case-based approach may be better used as an adjunct to existing regulations for Human Factors issues.

The purpose of this study is to illustrate how the design and deployment of a minimal protective system for multi-rotorcraft can cater for changes in legislation and provide for greater use both in and outdoors. A methodology is presented to evaluate the design and development of a system which protects both single axial and co-axial rotorcraft. The key emphasis of the development presented is the scenario in which the multi-rotorcraft can fly with increased speed including the capability of flying through windows and doors without the fear of system failure due to rotor disruption. Discussed as well is the degree of autonomy the reconfigurable system should feature as well as the effects of drag and added component mass to the performance of the system.

The purpose of this study was to assess at a preliminary level, the test/retest reliability of the math processing mini-game of CogGauge: a cognitive assessment tool for spaceflight. The focus of this assessment was on the stability of test scores and calculation of reliable change on test/retest scores obtained on a mathematical processing task. A sample of 18 neurotypical, non-concussed individuals with a minimum of a graduate or professional school degree completed the task on two separate occasions separated by 7 days. Test-retest coefficients, reliable change difference scores (including adjustments for practice effects) and descriptive statistics are provided along with a discussion of the CogGauge tool.

The assessment of situation awareness is modeled within a set-theoretic formalism. This formalism explicitly requires the identification of a functional relationship between particular sets of knowledge and specific performance criteria. The framework is exercised in an experiment, demonstrating the utility of the formalism.

This work presents an approach to enhance knowledge-based assistant systems in the domain of military helicopter missions with the ability to prevent the pilot from being overtaxed. Therefore, an estimation method for residual mental capacity and current subjective workload is proposed. This estimation enables the assistant system to deduce the pilots’ specific needs of support. As a result the assistant system shall be enabled to cooperate with the pilot by resource adaptive information exchange. First evaluation experiments of the prototype, conducted in our research helicopter mission simulator, will be described.

This text aims to present a study which deals with mental workload evaluation during task execution. It is focused on the Air Traffic Controllers working situation. In this document, we mainly introduce an experiment which has been conducted in a French En-Route air traffic center with the participation of Air Traffic Controllers. Four principal experiment characteristics are detailed: the experiment procedure, the working situation elaborated for our experimentation, the nature of the task achieved by participants, and the technique chosen to analyze mental workload felt by operators. We finally present the main results from our first data analysis which seem to confirm major observations known in the field of air traffic control, as well as, mental workload study field.

The notion of after action review (AAR) is known in the military where it is used to develop a common picture of what happened and why. Recently, the concept has been rediscovered by other domains. Obviously, a review within these domains would be different. This paper addresses development of an AAR engine. By “AAR engine” we mean a system that provides the common functionalities across all AAR systems into a single foundation for training. Regardless of the domain, there are capabilities needed in an AAR system (e.g. recording and playback of scenario data). On the other hand, there are also features specific for each domain. In this paper we first review the infrastructure of our AAR engine. Then advantages of such a system for addressing various AAR systems are reviewed. Additional advanced functions are then presented and reviewed in light of how the engine can easily provide these enhancements.

The Universität der Bundeswehr München is conducting research in the field of Manned-Unmanned Teaming (MUM-T). In the MUM-T scenario there is a human multi-UAV (Uninhabited Aerial Vehicle) operator who is responsible for the online air mission planning and re-planning. This operator shall be supported in his work by an assisting automation in order to maximize system performance. We therefore examine multiple scientific approaches to human-automation integration and present our established Cognitive and Cooperative Automation approach as well as a novel Cognitive Skill Merging approach. The latter is based upon bringing together human and machine cognitive skills in order to cooperatively reason about and work upon the common overall mission planning task without decomposing it in advance. The combination of these approaches results in the proposal of applying mixed-initiative planning to address the above-mentioned problem. The concept of the MUM-T Mission Planner is presented and future experiments are outlined.

The structural equation model is constructed to explore the relationship among basic cognitive abilities, personality traits and mental health of pilots. A framework of hypotheses is established to test the relationship among the three dimensions based on theories in the literature. Data is gathered from 65 pilots using 3 questionnaires. The model shows that both personality traits and mental health can affect the cognitive functions significantly, and that emotion characteristic, character traits and working attitude will also have an impact on a pilot’s basic cognitive ability by affecting his mental health state. The results suggest that not only flight cognitive abilities but also personality traits and mental health can affect a pilot in terms of flight performance.

Recent years have seen a surge of interest in game-based training by the military. Game-based simulation possesses a number of potential benefits including decreased testbed complexity and cost, increased agility regarding both software and hardware, and the possibility of increased effectiveness relative to traditional training methods. One area of weakness in game-based training is the difficulty in supporting an after action review (AAR). The paper explores the emerging problems faced by systems attempting to facilitate AAR in game-based training scenarios. It presents an architecture that addresses or circumvents these issues in a flexible and game-agnostic manner, and details the limitations introduced by such an approach. A discussion on future work leveraging the plugin-based SOCRATES architecture to augment video for improved training is included.