Three‐dimensional analysis of a driver‐passenger vehicle interface

This article presents a method of analyzing how drivers' anthropometric data are best accommodated by a specific driver‐vehicle interface. Three‐dimensional (3‐D) manikins with 18 links were developed using anthropometric data for the U.S. 95th percentile male and 5th percentile female. In addition, an adjustable seating buck was constructed to control 7 package variables. After the manikins were positioned in each driving environment, 3‐D Cartesian coordinates for the manikins' articulations were determined using a coordinate measuring machine. The data were then converted into joint angles to suggest suitable driving environments that consider appropriate driving postures. © 2004 Wiley Periodicals, Inc. Hum Factors Man 14: 269–284, 2004.     

A Human‐Oriented Simulation Approach for Labor Assignment Flexibility in Changeover Processes of Manufacturing Cells

Skilled operators are the most decisive key factors in manufacturing cells. An optimal assignment of operators is crucial for flexibility and productivity. Although there are many publications dealing with labor assignment problems, different forms of human cooperation on the shop floor and decentralized decision making, which are the main factors for system flexibility, are seldom concerned in existing models. In this article, a human‐oriented methodology to analyze, simulate, and evaluate labor assignment flexibility in changeover processes in manufacturing cells is introduced, which is characterized by an agent‐based approach. First, the problem architecture is presented along with the concepts of labor flexibility. Then, different types of human behavior in the changeover process are modeled. Furthermore, a human–machine interaction model is developed to integrate the human agent models into a generalized discrete event dynamic system (DEDS) process model. In this way, work process dynamics and cooperative behavior can be explicitly modeled and simulated. Third, the model is verified on the basis of a motorcycle engine manufacturing cell, and simulation experiments with different labor assignment schemes are designed and conducted. The simulation results show that assignment strategies incorporating different skill levels and cooperation styles have a significant impact on system performance. The agent‐based approach in conjunction with the human–machine interaction model can be used to analyze and solve a large class of assignment problems in flexible manufacturing systems, especially when human cooperation and collaboration are key factors shaping overall system performance.     

Cognitive control by brain-injured car drivers: an exploratory study

Cognitive control is a key tool for adaptation in dynamic situations. The aim of the study is to assess the relevance of a theoretical framework for cognitive control in dynamic situations, in order to understand brain-injured (BI) car drivers' cognitive impairment. The framework supports a cognitive control multimodality based on the crossing of two orthogonal dimensions: symbolic/subsymbolic; anticipative/reactive control. BI car drivers' behaviour was compared with that of a control group (CTRL) during driving simulator scenarios. Eye movement analysis, among other variables, revealed that BI car drivers made use of a more symbolic and reactive control than did CTRL drivers. CTRL drivers showed a more stable cognitive compromise than BI drivers. The latter became less symbolic and more reactive in the case of difficult scenarios. In addition, BI drivers focused on the main task of trajectory management, with fewer resources devoted to traffic interaction management.

Statement of Relevance:An explanation of differences between BI and CTRL drivers in terms of cognitive control requirements, attention and processing speed is put forward. From this, it is possible to derive some implications in terms of driver assistance (e.g. lane keeping or a warning assistance device) and rehabilitation.     

Relationships between driving simulator performance and driving test results

This article is considered relevant because: 1) car driving is an everyday and safety-critical task; 2) simulators are used to an increasing extent for driver training (related topics: training, virtual reality, human – machine interaction); 3) the article addresses relationships between performance in the simulator and driving test results–a relevant topic for those involved in driver training and the virtual reality industries; 4) this article provides new insights about individual differences in young drivers' behaviour. Simulators are being used to an increasing extent for driver training, allowing for the possibility of collecting objective data on driver proficiency under standardised conditions. However, relatively little is known about how learner drivers' simulator measures relate to on-road driving. This study proposes a theoretical framework that quantifies driver proficiency in terms of speed of task execution, violations and errors. This study investigated the relationships between these three measures of learner drivers' (n = 804) proficiency during initial simulation-based training and the result of the driving test on the road, occurring an average of 6 months later. A higher chance of passing the driving test the first time was associated with making fewer steering errors on the simulator and could be predicted in regression analysis with a correlation of 0.18. Additionally, in accordance with the theoretical framework, a shorter duration of on-road training corresponded with faster task execution, fewer violations and fewer steering errors (predictive correlation 0.45). It is recommended that researchers conduct more large-scale studies into the reliability and validity of simulator measures and on-road driving tests.     

Context‐Centric Speech‐Based Human–Computer Interaction

This paper describes research that addresses the problem of dialog management from a strong, context‐centric approach. We further present a quantitative method of measuring the importance of contextual cues when dealing with speech‐based human–computer interactions. It is generally accepted that using context in conjunction with a human input, such as spoken speech, enhances a machine's understanding of the user's intent as a means to pinpoint an adequate reaction. For this work, however, we present a context‐centric approach in which the use of context is the primary basis for understanding and not merely an auxiliary process. We employ an embodied conversation agent that facilitates the seamless engagement of a speech‐based information‐deployment entity by its human end user. This dialog manager emphasizes the use of context to drive its mixed‐initiative discourse model. A typical, modern automatic speech recognizer (ASR) was incorporated to handle the speech‐to‐text translations. As is the nature of these ASR systems, the recognition rate is consistently less than perfect, thus emphasizing the need for contextual assistance. The dialog system was encapsulated into a speech‐based embodied conversation agent platform for prototyping and testing purposes. Experiments were performed to evaluate the robustness of its performance, namely through measures of naturalness and usefulness, with respect to the emphasized use of context. The contribution of this work is to provide empirical evidence of the importance of conversational context in speech‐based human–computer interaction using a field‐tested context‐centric dialog manager.     

On distributed finite‐time observer design and finite‐time coordinated tracking of multiple double integrator systems via local interactions

This paper studies finite‐time coordinated tracking problem for multiple double integrator systems with a time‐varying leader's velocity and bounded external disturbances. We consider the dynamic feedback designs for two different cases. In the first case, the velocities of the followers and the leader are assumed to be unavailable, and the communication topology is assumed to be undirected and fixed. In the second case, the velocities of the followers and the leader are assumed to be available, and the communication topology is assumed to be directed and switching. Distributed finite‐time observers are designed, respectively, to obtain the velocity information in the first case and the relative state information in the second case. The states of these observers are then used to design control inputs that achieve finite time robust coordinated tracking of multiple double integrator systems in the presence of bounded disturbances for these two cases. Simulation results are provided to validate the effectiveness of these theoretical results. Copyright © 2013 John Wiley & Sons, Ltd.     

Remote human–robot collaboration: A cyber–physical system application for hazard manufacturing environment

Collaborative robot's lead-through is a key feature towards human–robot collaborative manufacturing. The lead-through feature can release human operators from debugging complex robot control codes. In a hazard manufacturing environment, human operators are not allowed to enter, but the lead-through feature is still desired in many circumstances. To target the problem, the authors introduce a remote human–robot collaboration system that follows the concept of cyber–physical systems. The introduced system can flexibly work in four different modes according to different scenarios. With the utilisation of a collaborative robot and an industrial robot, a remote robot control system and a model-driven display system is designed. The designed system is also implemented and tested in different scenarios. The final analysis indicates a great potential to adopt the developed system in hazard manufacturing environment.     

Coordinated control with multiple dynamic leaders for uncertain Lagrangian systems via self‐tuning adaptive distributed observer

This paper studies coordinated control of multiple Lagrangian systems with parametric uncertainties subject to external disturbances by proposing a fully distributed continuous control law based on the improved self‐tuning adaptive observer inspired by non‐identifier‐based high‐gain adaptive control technique. Under this distributed continuous control law, a group of Lagrangian systems are driven to the convex hull spanned by multiple heterogenous dynamic leaders, which can be any combination of step signals of arbitrary unknown magnitudes, ramp signals of arbitrary unknown slopes, and sinusoidal signals of arbitrary unknown amplitudes, initial phases, and any unknown frequencies. It is also worth to mention that this control law we propose, depending neither on any information of leader systems for uninformed followers, nor on external disturbances, even independent of neighbors' velocity, can achieve asymptotic tracking of multiple leaders without any additional condition instead of ensuring the ultimate boundedness of the containment error as in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

Pilot competencies as components of a dynamic human‐machine system

This paper formulates a theoretical model of flight deck team performance as a dynamic human‐machine system, later referred to as CRM‐DYMO (Crew Resources Management‐DYnamic MOdel). The model identifies human and machine subsystems. The human subsystem describes the activities taken by the flight crew and the machine subsystem describes the changes in the aircraft's state. The human subsystem's output forms an input for the machine subsystem, and the machine subsystem's output feeds back to the human system creating a closed loop system. Pilots’ performance are described as competencies, which form part of the elements in the human subsystem. This paper concentrates only on CRM competencies as defined by the International Civil Aviation Authority and the International Air Transport Association. In addition to the detailed conceptual model of the human subsystem and associated competencies, the approach is illustrated with reference to two accident case studies. These demonstrate how CRM‐DYMO can assist in analyzing CRM and help in identifying how the different system components interact. Although the case studies demonstrate the benefits of CRM‐DYMO, they merely serve as a starting point to understand how CRM works and will hopefully encourage supporting quantitative simulation modeling and empirical studies.     

Exploring crosstalk perception for stereoscopic 3D head‐up displays in a crosstalk simulator

In today's upper class vehicles, head‐up displays (HUDs) are state of the art human–machine interfaces used to increase driving security and comfort. Working with a stereoscopically perceived viewing impression, a novel automotive 3D HUD would allow the simultaneous visualization of multiple contents in various depth planes. However, stereoscopic crosstalk is one of the most important parameters influencing the image quality of stereoscopic systems. We present a setup to simulate crosstalk including a specific software solution. It constitutes a platform to explore the effects of stereoscopic crosstalk in the augmented reality viewing conditions of a 3D HUD. As the setup allows the variation of numerous parameters, it provides a versatile research platform. By means of it, we investigate the variation of the visibility and acceptability thresholds of crosstalk over various parameters. Our results include the finding that they decrease with rising contrast affirming this behavior known for conventional stereoscopic displays for stereoscopic see‐through displays.     

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates the use of diverse sensors, including computer vision, user‐generated content, and data from the learning objects (physical computing components), to record high‐fidelity synchronised multimodal recordings of small groups of learners interacting. We processed and extracted different aspects of the students' interactions to answer the following question: Which features of student group work are good predictors of team success in open‐ended tasks with physical computing? To answer this question, we have explored different supervised machine learning approaches (traditional and deep learning techniques) to analyse the data coming from multiple sources. The results illustrate that state‐of‐the‐art computational techniques can be used to generate insights into the "black box" of learning in students' project‐based activities. The features identified from the analysis show that distance between learners' hands and faces is a strong predictor of students' artefact quality, which can indicate the value of student collaboration. Our research shows that new and promising approaches such as neural networks, and more traditional regression approaches can both be used to classify multimodal learning analytics data, and both have advantages and disadvantages depending on the research questions and contexts being investigated. The work presented here is a significant contribution towards developing techniques to automatically identify the key aspects of students success in project‐based learning environments, and to ultimately help teachers provide appropriate and timely support to students in these fundamental aspects.     

A Comparative Study of Head‐Mounted and Table‐Mounted Augmented Vision Systems for Assembly Error Detection

Within the Cluster of Excellence “Integrative Production Technology for High‐Wage Countries,” a research project has been initiated to study self‐optimizing assembly cells and to design innovative ergonomic human–machine interfaces of the cell's numerical control. An experimental assembly cell was designed in which two robots carry out a certain repertoire of coordinated pick‐and‐place operations with small workpieces. To support the human operator while monitoring the operations and intervening in the case of assembly errors, an Augmented Vision System (AVS) has been designed and developed. The study described in this article deals with the ergonomic presentation of assembly information by the AVS to support the human operator in detecting assembly errors in small workpieces. Two laboratory experiments were carried out to compare two visual display types and to investigate different variations of presenting assembly information. Forty‐eight subjects participated in the experiments. The statistical analysis shows that the use of a head‐mounted display instead of a common table‐mounted display for the AVS increases the accuracy of assembly error detection significantly (α = 0.05). In contrast, a trend toward a longer detection time was found. © 2012 Wiley Periodicals, Inc.     

Distributed Fixed‐Time Coordinated Tracking for Nonlinear Multi‐Agent Systems Under Directed Graphs

This paper is concerned with the fixed‐time coordinated tracking problem for a class of nonlinear multi‐agent systems under detail‐balanced directed communication graphs. Different from conventional finite‐time coordinated tracking strategies, the fixed‐time approach developed in this paper guarantees that a settling time bound is prescribed without dependence on initial states of agents. First, for the case of a single leader, a distributed protocol based on fixed‐time stability techniques is proposed for each follower to accomplish the consensus tracking in a fixed time. Second, in the presence of multiple leaders, a new distributed protocol is proposed such that states of followers converge to the dynamic convex hull spanned by those of leaders in a fixed time. In addition, for a class of linear multi‐agent systems, sufficient conditions that guarantee the fixed‐time coordinated tracking are provided. Finally, numerical simulations are given to demonstrate the effectiveness of the theoretical results.     

An enhanced role model for alleviating the role‐binding anomaly

Roles and role models have received much attention as useful concepts for developing highly reusable and dynamically evolvable systems. Role models belong to the category of collaboration‐based development techniques, but most of the existing approaches to role models do not explicitly incorporate the core principle of collaboration‐based developments as an essential property of their primary design goals. Consequently, the existing approaches still suffer from a problematic phenomenon that the structural and behavioral constraints defined in a role system can be violated during the role‐binding stage. We call such a problematic phenomenon the role‐binding anomaly. In order to alleviate the role‐binding anomaly, we propose an enhanced role model, in which all role instances and core objects can exist by themselves, namely, they can be developed, executed, and tested independently. Roles and core classes can be bound to each other at the instance level. In addition, the role system describes and encapsulates the behavior for dynamic reconfigurations among role instances. The enhanced role model is designed so as to be meaningful with respect to software engineering principles, rather than dynamic evolution. It also facilitates role model implementation using general programming languages (i.e. not supporting dynamic specialization) such as Java. To illustrate how the proposed role model makes such benefits, we develop a set of Java classes necessary for implementing the enhanced role model in the form of a Java package role, and present a simplified automatic teller machine system as an example application. Copyright © 2002 John Wiley & Sons, Ltd.     

Situation awareness assessment in critical driving situations at intersections by task and human error analysis

The rapid development of sensor and tracking technology enables deployment of new Advanced Driver Assistance Systems (ADAS) that support the driver not just on highways but in urban areas as well. Intersections particularly present critical traffic scenarios where almost 35% of accidents occur, partially due to the present lack of in‐depth research about human errors and their determinants. The first step in ergonomic design of ADAS is to identify the specific situations in which drivers require support. To contribute to identification of such spots, situation awareness of 20 drivers in four critical intersection scenarios was explored. The study was conducted in the fixed‐base driving simulator. The applied approach consisted of assessing drivers' expectations and mental workload and of comparing theoretically correct cognitive behavior to experimentally collected data. Intersection scenarios were divided into five segments, and for each segment a task analysis was made. The study has shown that the driving simulator environment can be successfully deployed to provoke and explore various driver errors. The results have revealed that, in scenarios in which information is objectively missing, the majority of errors happened because the drivers had inaccurate mental models of particular scenarios. To the contrary, in the complex scenario the major cause of accidents was information overload. Furthermore, the task analysis disclosed applicable areas of intersection assistance. © 2010 Wiley Periodicals, Inc.     

Towards a cognitive approach to human–machine cooperation in dynamic situations

Human-computer interaction research has produced consistent results bearing on a well-established body of knowledge in cognitive science. In contrast, the new research domains of computer- supported cooperative work (CSCW) or human–machine cooperation are harder to develop because the problems to be solved are more complex and the theoretical frameworks more heterogeneous. However, dynamic situations with high temporal constraints create occasions where small teams (including humans and machines) can cooperate on an almost cognitive basis, reducing social or emotional effects. This paper reviews the state of the art on cognitive cooperation to extend an individual cognitive architecture and deal with these situations, combining private and cooperative activities that are highly task-oriented. Cooperation is taken as the management of interference between individual activities to facilitate the team members' sub-tasks and the team's common task when there is one. This review of the literature is a step towards a theoretical approach that could be relevant to evaluate cooperation and to design assistance in diverse domains such as air traffic control or aircraft piloting.     

Computer‐aided macroergonomics for improved performance and safety

The U.S. presidential election of 2000 was characterized by alleged ergonomic problems associated with the design of voting ballots. However, this visible event actually exemplified the fact that many apparent ergonomic issues are, in fact, macroergonomic issues. That is, in such cases, there are larger systemic factors at work that interact with and contribute to human–machine interface issues. Further complicating system effectiveness is the notion that modern work systems are distributed and therefore require computer aiding to establish a communication pipeline through which decisions can flow and performance can be enhanced. A conceptual and theoretical framework is presented for understanding such computer‐aided work systems and a taxonomy and research examples for three types of computer‐aided work systems are also offered. It is concluded that the single operator–single machine paradigm is not obsolete and the focus remains ultimately on the ergonomic level, but relevant macroergonomic, sociotechnical system factors require consideration prior to optimizing this level for overall ergonomic success. © 2002 Wiley Periodicals, Inc.     

Vision‐based control architecture for human–robot hand‐over applications

Human–robot collaboration will be an essential part of the production processes in the factories of tomorrow. In this paper, a human–robot hand‐over control strategy is presented. Human and robot can be both giver and receiver. A path‐planning algorithm drives the robotic manipulator towards the hand of the human and permits to adapt the pose of the tool center point of the robot to the pose of the hand of the human worker. The movements of the operator are acquired with a multi 3D‐sensors setup so to avoid any possible occlusion related to the presence of the robot or other dynamic obstacles. Estimation of the predicted position of the hand is performed to reduce the waiting time of the operator during the hand‐over task. The hardware setup is described, and the results of experimental tests, conducted to verify the effectiveness of the control strategy, are presented and discussed.     

A screen‐mottling inspection and analysis system for CRT‐manufacturing quality control

Abstract— A screen‐mottling inspection and analysis system for CRT manufacturing has been developed for in‐factory quality control. This system is capable of translating the implicit knowledge of mottling judgement by the human eye to a quantitative and explicit knowledge through a machine. Screen‐mottling judgement by the human eye has always been argumentative and subjective to personal sensitivity. With the successful development of a CRT‐screen‐mottling checker, an accurate and consistent reading of ±0.1 units on a scale that ranges from 1.0 to 3.0 can be achieved. This eliminates the fluctuations of human judgement. To the authors' knowledge, there are a few mottling analysis systems used in non‐display‐related industries which only capture and analyze flat reflective surfaces. These systems cannot be used for CRT displays because of the non‐uniform glass thickness and curvature of the glass. This newly developed CRT‐mottling checker system is probably one of the first checkers for the CRT industry.     

Driver's distracted behavior: The contribution of compensatory beliefs increases with higher perceived risk

Engaging in distractive behaviors while driving is common worldwide, despite its proven negative impact on driving safety. The current study aimed to investigate the ability of drivers' compensatory beliefs regarding distracted driving (i.e., the belief that the negative effects of an unsafe behavior can be “neutralized” by engaging in another safe behavior; e.g., “slowing down can compensate for the impact of driving distractions”) and drivers' risk perceptions to predict drivers' distracting behaviors. This study analyzed the self-reports of 304 non-professional drivers (186 males and 118 females) between the ages of 19 and 66 years. The revised questionnaires were proven reliable and valid for measuring drivers' compensatory beliefs regarding distractions, their distractive behaviors, and their perceived risk. Additionally, three components (i.e., mobile phone use, in-vehicle interactions, and mind wandering) were identified in the current study using factor analyses. The analysis of the relationships among the study variables showed that the drivers' compensatory beliefs regarding distractive behaviors were a core predictor of the drivers’ engagement in distracting behaviors, especially for behaviors with a higher perceived risk rating (e.g., mobile phone use).