Design Of Human-machine Systems Research Articles

No robot is an island - what properties should an autonomous system have in order to be resilient?

Autonomous systems are inherently designed to be self-sufficient only under particular circumstances, for specific activities. The environment needs to be tailored to align with these design boundaries, ensuring that technical systems operate as intended. This paper proposes that insights from resilience engineering can enhance the self-sufficiency of so-called autonomous systems, consequently bolstering their adaptive capacity in unforeseen or unpredicted scenarios. Two cases of autonomous systems are examined to illustrate how this enhancement can be achieved. The conclusion drawn is that the resilience envelope of a system can be augmented by enabling the system to adapt to multiple design cases, by defining and prioritizing the core values of the system, and by designing the system to possess a framework for situations rather than being confined to a singular situational frame. The implications for the design of human-machine systems are also discussed.

A Team Cognition Measurement Method for Single Pilot Operations Human-Machine System Design

Team cognition is an important indicator to reflect the trend of single pilot operation (SPO) human-machine system team performance. How to measure team cognition to explore different function allocation decisions before the implementation of prototypes or simulators has become a significant step in the early SPO human-machine system design. Therefore, this article proposed a team cognition measurement method based on the social network analysis (SNA) method, namely cognitive social network analysis (CSNA). The CSNA method firstly identified the nodes, edge directions and channel resource values of each task; secondly calculated the cognitive demands of each task based on multiple resource theory; thirdly summed the cognitive demands of the same task to construct the association matrix; and finally calculated global and nodal network metrics. The results of the study showed that (1) the CSNA method could identify design flaws of the initial SPO human-machine system; (2) the CSNA method increased the ability to identify the changes in both the cognitive demands of tasks and the overall workloads of human agents compared to the SNA method; (3) the CSNA method could help researchers make reasonable design suggestions to improve the team performance of the redesigned SPO human-machine system. The above results not only verify the feasibility of the CSNA method, but also show that the CSNA method is superior to the current SNA method.

DESIGNING HUMAN-MACHINE SYSTEMS: TRANSFORMATION OF A DESIGNER’S THINKING

Industry 4.0 became a powerful impetus for the development of man-machine systems, which, on the one hand, increased their efficiency and reliability and, on the other hand, made them super-complex. As a result, this led to an increase in the complexity of human-machine system management and the manifestation of the human factor. The consequence is that, currently, the main cause of accidents and disasters is the human factor. Thus, the safety of human-machine systems largely depends on the person's psychological and physiological characteristics. The article shows that the study of a person's characteristics is the basis for the development of a human factor management system. The essential element of the human factor management system is the systemic ergonomics thinking of the human-machine systems designer. This type of thinking is formed as a result of training and the gradual acquisition of eco-ergonomic design skills. To explain the importance of the formation of eco-ergonomic thinking in human-machine systems design, eco-ergonomic thinking evolution is presented in the work. Through the analysis of the sequence of the development of ergonomic thought, it is shown how the approach to ensuring the safety of human-machine systems has changed from the middle of the 20th century to the present. The next stage of the work was the analysis of eco-ergonomic, human-oriented, risk-oriented, and strategic thinking. Based on the analysis results, a hierarchy of thinking types is built, and their role in the formation of systemic ergonomics thinking in human-machine systems designing is shown. The main feature of the designer’s systemic ergonomics thinking is the priority of finding a solution to the problem in the system operation through research and analysis of human-machine interaction. Based on the obtained results, the importance of the formation and development of systemic ergonomics thinking is substantiated. It is shown how to implement the formation of a designer's systemic ergonomics thinking of human-machine systems through the training system.

A Corpus-Based Study on Feedback in Daily Conversation: Forms, Position and Contexts.

Understanding how feedback is employed in various forms, positions, and contexts can provide valuable insights into improving communication and the design of human-machine dialogue systems. This paper aims to deepen the understanding of feedback in daily conversation and investigate how feedback is employed in various linguistic forms, position, preceding and following contexts, using a large corpus of telephone conversations. The study identifies three subclasses of feedback, including understandings, agreements, and answers, which account for almost one-third of the total utterances in the corpus. Acknowledge (backchannel) is the most frequently used subtype of feedback, accounting for almost 60% of the feedback, and is primarily used for conversational management and maintenance. Assessment/appreciation, on the other hand, is used less frequently, accounting for less than 10% of feedback, and is mainly realized by more creative, unpredictable, longer forms. The analysis also reveals that speakers are intentional in distinguishing the three subclasses of feedback based on various variables, such as position and the proximal discourse environment. Furthermore, the three subclasses of feedback are restricted by the function ofpreceding contexts, which shape the length of the remaining turn. The study suggests that future research should focus on exploring the individual differences and investigating the possible variations across different cultures and languages.

ERGONOMIC THINKING IN THE DESIGN OF HUMAN-MACHINE SYSTEMS

In the era of Industry 4.0, human-machine systems have become highly complex and contain a large number of elements and sources of information. It increases the complexity of human-machine system management, which leads to the manifestation of the human factor phenomenon. The consequence is that currently, 70% to 90% of accidents and disasters are related to the human factor. Therefore, the safety of human-machine systems largely depends on human abilities, cognitive, behavioral, and psycho-physiological features. It is shown that the study of individual characteristics of a person will allow the management of the human factor in the human-machine system. The crucial point of human factor management is the availability of systemic ergonomic thinking in the designer of the human-machine system. The formation of such thinking is connected with learning and the gradual acquisition of the necessary knowledge and skills. To understand the principles of ergonomic thinking formation, the evolution of ergonomic thinking in the design of human-machine systems is shown. Due to analysis of the sequence of ergonomic thought development, it is shown how approaches to ensuring the safety of human-machine systems have been rethought from the middle of the 20th century until now. Currently, the global social processes and technologies of Industry 4.0 have fundamentally changed the concept of “work”, parameters of the labour market, and safety requirements and caused the emergence of a new model of the labour paradigm “Work 4.0”, which, in turn, became the driver of the revision of the concept of “workplace” established in society and the emergence of the digital workplace. The article presents the definition of a “digital workplace” and analyses its essential characteristics. The next stage of the work was a model of the structure of the engineer’s ergonomic thinking, the main feature of which is the priority of solving the problems of human-machine interaction. The work also shows that ergonomic thinking is one of the elements of safety culture. In combination with other elements such as a human-centered approach, ecological thinking and others, ergonomic thinking creates a space of a safety culture. Based on the presented results, the importance of engineers’ ergonomic thinking is substantiated. It is shown how to implement the formation of ergonomic thinking through the training system.

Effect of verbal messages with reminders to communicate driving situations to alter driver behavior in conditional driving automation

In conditionally automated driving, drivers are relieved of steering (hands-off), accelerating, and braking actions as well as of continuous monitoring of driving situations and the system operation status (eyes off). This enables continuously engagement in non-driving-related activities. Managing the allocation of a driver’s attention to the surrounding environment and automation status presents a major challenge in human–machine system design. In this study, we propose a verbal message with a reminder (monitoring request) to divert the driver’s attention from non-driving-related activities to peripheral monitoring under conditionally automated driving. When the system encounters events related to weather, traffic, and road geometry, it provides a verbal message pertaining to the road surroundings (e.g., “It is foggy outside”) to the driver. After three seconds, the system provides a reminder message (i.e., “Did you confirm it?”) to the driver. We explore two questions: (1) how does the message with the reminder affect the driver’s attention allocation, and (2) how does the message with the reminder affect the driver behavior in response to a request to intervene (RTI). With a driving simulator, we designed a repeated measures mixed design with a between-participant factor of “Driving condition” and within-participant factors of “Event type” and “Measurement time”. Three driving conditions were established as follows: no messages, messages without reminders, and messages with reminders. Twenty-seven drivers participated as participants in the driving simulator experiment. Results showed that the reminder message was effective in allocating the participants’ attention to the surrounding environment, and the participants took over the driving task after spending more time understanding the take-over situation in the condition of messages with reminders compared to those in the condition of no messages. We conclude that the proposed reminder message can direct drivers’ attention to the road surroundings during conditionally automated driving. In the future, we plan to design adaptive verbal monitoring requests to adjust the reminder message according to the situation.

From Human-Human to Human-Machine Cooperation in Manufacturing 4.0

Humans are currently experiencing the fourth industrial revolution called Industry 4.0. This revolution came about with the arrival of new technologies that promise to change the way humans work and interact with each other and with machines. It aims to improve the cooperation between humans and machines for mutual enrichment. This would be done by leveraging human knowledge and experience, and by reactively balancing some complex or complicated tasks with intelligent systems. To achieve this objective, methodological approaches based on experimental studies should be followed to ensure a proper evaluation of human-machine system design choices. This paper proposes an experimental study based on a platform that uses an intelligent manufacturing system made up of mobile robots, autonomous shuttles using the principle of intelligent products, and manufacturing robots in the context of Manufacturing 4.0. Two experiments were conducted to evaluate the impact of teamwork human-machine cooperation, performance, and workload of the human operator. The results showed a lower level of participants’ assessment of time demand and physical demand in teamwork conditions. It was also found that the team working improves the subjective human operator Know-how-to-cooperate when controlling the autonomous shuttles. Moreover, the results showed that in addition to the work organization, other personal parameters, such as the frequency of playing video games could affect the performance and state of the human operator. They raised the importance of further analysis to determine cooperative patterns in a group of humans that can be adapted to improve human-machine cooperation.

How to use human pose estimation to measure the hand-arm motion in craft application with no influence on the natural user behavior

The interaction between human and machine plays an important role in the design and optimization of human-machine systems. This interaction is characterized by human motion using the technical system. Especially in the field of hand and power tool applications, the motion capture should be performed under the real working condition and without influencing the user. There are already motion tracking systems that allow capturing the motion during the interaction, but there is no mobile motion capture system that allows an individual analysis of the user for biomechanical analysis in the normal work process without influencing him. Therefore, requirements for a motion capture system are derived and a system is presented that meets these requirements. This system consists of two cameras and is based on the pose estimation algorithm OpenPose. The comparison of the presented system and the state-of-the-art system Xsens is performed and based on the measured elbow angle and the wrist position. The results show a very good correspondence between the curve characteristic of the elbow angle and the wrist position of both systems. However, inexplicable values shifting at two different levels still occur, which need to be investigated further. Overall, the presented system shows great potential in terms of mobility and flexibility of the presented system with some weaknesses in the data processing and efficiency. By addressing these weaknesses, the presented system can be used in the analysis and optimization of human-machine systems.

Auditory versus visual spatial stimulus-response mappings in tracking and discrete dual task performance: implications for human-machine interface design

A discrete four-choice response task with auditory signal presentation and a joystick-controlled visual tracking task was used to investigate how spatial compatibility influences the dual-task performance of different display-control settings. It was found that the more incompatible the stimulus-response mapping, the longer the delay for both tasks, presumably because of the longer stimulus encoding time required for the incompatible conditions. A comparison of the findings of this study with those of past experiments on visual visual setting shows that the dual-task performance in a cross-modality (auditory visual) setting was significantly better than that in an intra-modality (visual visual) setting because of visual scanning required in the intra-modal dual tasks. However, when the locations of visual visual tasks were close enough such that ambient and focal vision was concurrently used for information processing, the dual-task performance of intra-modality (visual visual) configuration was slightly better than that of the cross-modality (auditory visual) configuration. Practitioner Summary: The effect of spatial compatibility with auditory signal presentation in multiple display-control configurations was examined in a dual-task paradigm. The results provided important and useful ergonomics design implications and consequent recommendations for intra- and cross- modal interface design. The results should facilitate human-machine system design and improve overall system performance.

시각자극의 배열 방향과 순서에 따른 인간의 자극 인지 특성

Objective: The purpose of this study is to find out how the arrangement of visual stimuli affects human perception.BRBRBackground: The correct perception of visual information in the design of human-machine systems is one of the most important factors to consider for improving the usability and safety of systems. In particular, the arrangement direction and order of visual stimuli are design elements that should be considered important in the design of visual information or in the design of the user interface.BRBRMethod: Three black circles were used as an experimental stimulus. The reference stimulus was a 30mm diameter circle and the signal stimulus was a 30.8mm diameter circle. The signal stimulus was the size that 90% of the subjects correctly determined in the JND measurement experiment. The experimental equipment was a tachistoscope and 20 college students participated as subjects. The subjects judged whether the three circles presented in the horizontal or vertical direction were the same size. They pressed the left button if they were the same and pressed the right button for the other.BRBRResults: Although the difference was not statistically significant, the accuracy of men

THE ROLE OF THE ERGONOMICS ON APPAREL SECTOR WITHIN THE DEVELOPING TECHNOLOGY

On every stage of our life, we observe technological developments on the products and communication instruments we use. In the world of technology that changes rapidly “Will the role of the ergonomics on design of human-machine systems lose its effect?” question might come to mind. We can declare that with the technological development all over the world, as a practical science the ergonomics, that should be benefited from, will not lose its importance, the intensity of the research will increase from the physical ergonomics towards the cognitive ergonomics. With the technological development, in fact the human benefits from the technological change while evaluating the systems those include many parameters, but the last decision maker is human as usual -and as in all the automatic systems- the human maintains its crucial role in every kind of system. It is possible to state that hybrid human-machine systems those compose of various elements and can be solved, when needed, with deterministic, probabilistic and fuzzy models will become more complex via high level technology. For instance, if the humans and the robots are working together in a production system, in case of a malfunction in production, a robot that does not stop like human might cause much bigger destruction in production or business systems security. In this study, we tried to examine from various perspectives the changing process and the role of the ergonomics in apparel sector’s business life within the technological development over the world.

A Systematic Review of Physiological Measures of Mental Workload.

Mental workload (MWL) can affect human performance and is considered critical in the design and evaluation of complex human-machine systems. While numerous physiological measures are used to assess MWL, there appears no consensus on their validity as effective agents of MWL. This study was conducted to provide a comprehensive understanding of the use of physiological measures of MWL and to synthesize empirical evidence on the validity of the measures to discriminate changes in MWL. A systematical literature search was conducted with four electronic databases for empirical studies measuring MWL with physiological measures. Ninety-one studies were included for analysis. We identified 78 physiological measures, which were distributed in cardiovascular, eye movement, electroencephalogram (EEG), respiration, electromyogram (EMG) and skin categories. Cardiovascular, eye movement and EEG measures were the most widely used across varied research domains, with 76%, 66%, and 71% of times reported a significant association with MWL, respectively. While most physiological measures were found to be able to discriminate changes in MWL, they were not universally valid in all task scenarios. The use of physiological measures and their validity for MWL assessment also varied across different research domains. Our study offers insights into the understanding and selection of appropriate physiological measures for MWL assessment in varied human-machine systems.

Characteristics of the psychophysiological state of a human operator in the information system “human — display”

The paper describes the structural model of a human operator, who perceives information from the display screen. The method for measuring visual fatigue in terms of the stability of clear vision was investigated and developed. The characteristics of attention were investigated. The programs that automate the measurement of visual fatigue and attention were developed. Different types of memory were considered. A structural model of memory is presented, based on which a method has been developed and experiments have been conducted to study the perception of symbolic information from a display screen by a human operator. The results obtained can be used in the design and operation of information human-machine systems.

Heart-Computer Synchronization Interface to control human-machine symbiosis: a new human availability support for cooperative systems

The paper proposes an original architecture to control human-machine symbiosis by using Heart-Computer Synchronization Interfaces (HCSI). This symbiosis depends on the limits of three autonomy prerequisites: the knowledge required to treat a situation, the availability of the human and technical resources when achieving tasks, and the possibilities to act by using dedicated interfaces. As inattention is one the causes of a lack or a loss of the symbiosis related to human availability, the new system consists in controlling it by studying the impact of the synchronization of dynamic event occurrence with heart rate. The results of an exploratory study are relevant and promising: subjects for who the activation of visual and sound alarms were synchronized with heartbeats made significantly more perception errors than subjects for who this activation was not synchronized. They demonstrate that the design of human-machine systems has to be aware of such synchronization that may affect human perception abilities and degrade the efficiency of the cooperative activity achievement. This is then a new challenge for defining future cooperative systems based on human availability supports to perceive data from automated tools.

A Continuous and Quantitative Metric for the Levels of Automation

The standard SAE J3016 provides a definition for levels of driving automation; however, shared control algorithms that have successfully been applied to vehicle automation, do not reasonably fit into the levels proposed by the standard. In this paper, the rich literature about levels of automation taxonomies is reviewed regarding the applicability to all automation concepts. Most definitions provide qualitative rankings of different levels of automation for specific applications. However, from an engineering perspective, a quantitative and generic approach would generate great benefit for the design, analysis and evaluation of human-machine systems. Thus, criteria for a desirable metric of levels of automation are discussed and a continuous and quantitative measure based on the options available to the human is proposed. The application to an advanced driver assistant system example is demonstrated and future ways to leverage the potential of the metric within and beyond automated driving are examined.

Learning Timed Automata from Interaction Traces

The design of load-critical human-machine systems presumes thorough modelling and analysis of interaction profiles the systems are meant to withstand at peak loads. The need for mathematical modelling of interactions is often ignored due to significant modelling effort and lack of relevant tools. We propose an algorithm for automatic learning a subclass of Uppaal timed automata models from system and its environment interaction logs. The learning method relies on synchronous communication assumption that is characteristic to communication protocols of networked HMS distributed components. The method is demonstrated on IEEE1394 protocol learning example. Beside enhancing automatic test generation, the learned model allows verifying test feasibility and test optimization already in early phases of test design.

Human-machine interaction and health at work: a scoping review

Human-machine interaction (HMI) in industrial work processes has been an important topic during the last decades, but the latest technological developments such, as for example, cyber-physical systems and increasingly shorter innovation cycles in this field pose new challenges to the design of human-machine systems and highlight the enduring importance of the subject. This paper presents the main results of a review on HMI and health at industrial workplaces using the scoping review methodology. The review prepared is based on 102 studies covering aspects of function allocation, interface and interaction design, as well as operation and supervision of systems. Results of the review process and on function allocation, in particular, as an important feature of HMI, are discussed in detail. The results show that mainly aspects of well-being and performance are discussed in literature within the context of function allocation. Furthermore, the scoping review reveals a research need for HMI and mental health at work as well as a need for more comparable research designs.

Human-machine interaction and health at work: a scoping review

Human-machine interaction (HMI) in industrial work processes has been an important topic during the last decades, but the latest technological developments such, as for example, cyber-physical systems and increasingly shorter innovation cycles in this field pose new challenges to the design of human-machine systems and highlight the enduring importance of the subject. This paper presents the main results of a review on HMI and health at industrial workplaces using the scoping review methodology. The review prepared is based on 102 studies covering aspects of function allocation, interface and interaction design, as well as operation and supervision of systems. Results of the review process and on function allocation, in particular, as an important feature of HMI, are discussed in detail. The results show that mainly aspects of well-being and performance are discussed in literature within the context of function allocation. Furthermore, the scoping review reveals a research need for HMI and mental health at work as well as a need for more comparable research designs.

A method for designing levels of automation based on a human-machine cooperation model

Human-machine systems are omnipresent in our everyday life. These systems are very important; they allow human and machine understanding and working together efficiently. But poor choices during its design can have important impacts, principally in terms of safety, security and performance. The design of human-machine systems takes into account the human factors, and both human and machine limitations and abilities through the levels of automation. Therefore, it is needful for the design of such systems to do a preliminary study regarding the possible interactions between human and machine. In this context, we are interested in robotic domain especially in the supervision and control of a self-organized swarm of robots adapted for the human needs. This paper illustrates a methodological approach based on a human-machine cooperation model used to identify different interactions between human and robot and then to define adequate levels of automation taking into account the capacities and abilities of both human and robot according to the situation.

Intuitive Cognition and Models of Human-Automation Interaction.

The aim of this study was to provide an analysis of the implications of the dominance of intuitive cognition in human reasoning and decision making for conceptualizing models and taxonomies of human-automation interaction, focusing on the Parasuraman et al. model and taxonomy. Knowledge about how humans reason and make decisions, which has been shown to be largely intuitive, has implications for the design of future human-machine systems. One hundred twenty articles and books cited in other works as well as those obtained from an Internet search were reviewed. Works were deemed eligible if they were published within the past 50 years and common to a given literature. Analysis shows that intuitive cognition dominates human reasoning and decision making in all situations examined. The implications of the dominance of intuitive cognition for the Parasuraman et al. model and taxonomy are discussed. A taxonomy of human-automation interaction that incorporates intuitive cognition is suggested. Understanding the ways in which human reasoning and decision making is intuitive can provide insight for future models and taxonomies of human-automation interaction.