Next Generation Universal Ground Control System HMI Design

The current paper presents the results of the evaluation of a novel human machine interface for supervision and guidance of multiple highly automated unmanned aircraft. Accidents of unmanned aircraft are often related to deficiencies in the design of the human machine interface. Many of these deficiencies are a consequence of insufficient consideration of human factors engineering principles in the early stages of system development. Therefore, in the design of the current human machine interface, empirically validated human factors methods were applied in order to optimally support a remote pilot in supervising and guiding multiple highly automated unmanned aircraft. An information management concept was developed that allows for an increase in the number of UAS that are being supervised without considerably increasing display complexity. In order to evaluate the human machine interface, two within-subj ect simulation studies were conducted. In both studies, pilots were asked to supervise and guide a varying number of UAS in several experimental scenarios using the new human machine interface. Following the experimental scenarios, a structured interview regarding the design of the human machine interface was conducted. The objective of the first study was to gather initial data on the general usability of the interface. The aim of the second simulation study was to investigate how increasing the number of UAS from one up to five affects the time that a pilot needs to acquire and change specific system parameters of any UAS under supervision. Further, the impact of increasing the number of UAS on pilot workload and situation awareness was assessed. The results of the interviews suggest that the design concept of the human machine interface is feasible and easy to understand. The information management concept was described as reasonable and logical. Important information was accessible quickly and (critical) system states could easily be identified. No significant effects of increasing the number of UASs to be supervised on reaction, workload or situation awareness were observed. The findings suggest that the information management concept is reasonable and usable.

With more and more systems and machines operating autonomously, the role of the operator is changing from “being actively in control” to “monitor and intervene”. Human Machine Interfaces (HMI) therefore need to be optimized so that they can efficiently be monitored by a human. We propose the Human Efficiency Evaluator (HEE), a software tool for (1) evaluating the impact of HMI design changes on the visual monitoring behavior of the operator and (2) to explore differences in understandings between a group of collaborating HMI designers or between HMI designers and their targeted audience: the operators. We describe the tool and highlight the model exploration capabilities of the HEE by reporting about two use cases: one in the maritime domain, in which the tool supported an HMI designer to get insights into human operators’ monitoring behavior, and one in the automotive domain, in which the tool was used to reveal differences in understanding between six Human Factor Experts about the impact of three HMI design variants of an Urban ACC.

The Human Machine Interface (HMI) design is a critical field of work because no general guidelines or rules have been assessed. In order to aid practitioners to design effective HMIs, different methodologies have been studied. To understand task objectives and plan goal-oriented actions, human operators exploit specific cognitive processes that have to be supported with advanced interfaces. Including cognitive aspects in HMI design allows generating an information flow that reduces user mental workload, increasing his/her situation awareness. This paper will explore a real designing phase of a Graphical User Interface (GUI) for the telenavigation of a space rover that makes the cognitive process of the user a priority in relation to the other development guidelines. To achieve this, the method described in this paper combines a Cognitive Task Analysis (CTA), known as Applied Cognitive Work Analysis (ACWA), with a multi-agent empirical test to ensure the GUI effectiveness. The ACWA allows to evaluate mission scenarios, i.e. piloting the rover on the Mars surface, in order to obtain a model of the human cognitive demands that arise in these complex work domains. These demands can be used to obtain an effective information flow between the GUI and the operator. The multi-agent empirical test, on the other hand, allows an early feedback on the user mental workload aiming to validate the GUI. The result of the methodology is a GUI that eases the information flow through the interface, enhancing operator’s performance.

Modern production systems are becoming more and more complex to comply with diversified market needs, flexible production, and competitiveness. Despite technological progress, the presence of human operators is still fundamental in production plants, since they have the important role of supervising and monitoring processes, by interacting with such complex machines. The complexity of machines implies an increased complexity of human–machine interfaces (HMIs), which are the main point of contact between the operator and the machine. Thus, HMIs cannot be considered anymore an accessory to the machine and their improvement has become an important part of the design of the whole machines, to enable a nonstressful interaction and make them easy to also use less skilled operators. In this article, we present a general framework for the design of HMIs that adapt to the skills and capabilities of the operator, with the ultimate aim of enabling a smooth and efficient interaction and improving user’s situation awareness. Adaptation is achieved by considering three different levels: perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). For each level, general guidelines for adaptation are provided, thus defining a meta-HMI independent of the application. Finally, some examples of how the proposed adaptation patterns can be applied to the case of procedural and extraordinary maintenance tasks are presented. Note to Practitioners —This article was motivated by the problem of facilitating the interaction of human operators with human–machine interfaces (HMIs) of complex industrial systems. Standard industrial HMIs are static and do not consider the user’s characteristics. As a consequence, least-skilled operators are prevented from their use and/or have poor performance. In this article, we suggest a novel methodology to the design of adaptive industrial HMIs that adapt to the skills and capabilities of operators and compensate their limitations (e.g., due to age or inexperience). In particular, we propose a methodological framework that consists of general rules to accommodate the user’s characteristics. Adaptation is achieved at three different levels: perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). The presented rules are independent of the target application. Nevertheless, we establish a relationship between such design rules and user’s impairments and capabilities and kind of working tasks. Hence, designers of HMIs are called to instantiate them considering the specific requirements and characteristics of the users and the working tasks of the application at hand.

The number of man-months of HMI (human machine interface) development for embedded systems is increasing because of internationalization. Even though functions of embedded systems such as in-vehicle systems are largely the same for each country, the HMI design has to be customized to specific languages and requirements. For instance, adjusting the width and font of text improves its visibility. However, this creates a new issue regarding HMI design management. We report here on HMI development of derived products, which are assumed to be developed with common functions and customized HMI, by using a model-driven prototyping tool for in-vehicle systems. The prototyping tool we developed is based on open source software including an image editor, Eclipse plug-in, relational database, servlet, and Web browser. In addition, XML for the prototyping tool is defined in order to represent derived product support features. In experiments, this prototyping tool enabled HMI designers of an in-vehicle system to check the HMI design more quickly and easily than in a traditional HMI development process.

ABSTRACTA human operator monitoring a safety-critical system has to perceive information quickly and accurately to detect critical system states and execute countermeasures in time. So far, testing such human machine interfaces (HMIs) is a complex task as HMI design prototypes have to be implemented for simulation environments to perform tests with professional operators. We propose Konect Value, a quantitative method to estimate the relative perception accuracy and operator reaction time at an early design stage. The model-based method solely requires a task model and HMI design sketches as input. To validate the Konect Value, we applied the quantitative measure to seven different HMIs in a truck platooning use case. A comparison of the calculated value to the measured accuracy and reaction times in a lab study (n=33) revealed high correlations for the relative reaction time (r=0.83, p<0.05) and relative perception accuracy (r=−0.90, p<0.01). This indicates that Konect Value is a promising method for early HMI design evaluation in the safety-critical system domain.

Design of main control room (MCR) should be appropriate to the system features and user characteristics to enable operator conducting more safe and reliable reactor operation tasks. Considers the digital based systems are employed in the control room of the current reactor design, the large display panels and operator control consoles are the essential elements of the human machine interfaces (HMI). The paper discusses the design process of HMI for single unit of modular reactor, including the control room components arrangement. The10MWt of high temperature gas cooled reactor type design considered has sufficient information data for conducting HMI design process was used to represent the unit of modular reactor in this study. HMI design in the control room covers two main function areas which are reactor system and conventional island. In this paper the discussion was emphasized on the HMI design for reactor system. The method applied in the development process is based on the NUREG-711 and ISO 11064-1. The results obtained from identification of reactor system characteristics and operation based on the conceptual design document, basic design, and further discussions with the design developers are used in constructing of HMI design. The preliminary HMI design was integrated in the control room which consists of large display panel, control consoles and supervisor workstation, where the structure and hierarchy are applied based on its functions. The information hierarchy and design consistency are important especially for the HMI of multi modules reactor. Moreover, additional information displays are also required to ensure the essential information can be presented appropriately. The large display panels of the designed HMI composed of large screen displays, mimic displays and alarm tiles employed as a tool to present outline information of the plant. Three operation personnel were set to conduct operation task in the control room. The design obtained in this stage is not enough detail, however it can be further developed and modified according the completeness of reactor information data.

Human-machine interface (HMI) design of the main control room (MCR) can obviously affect efficiency, safety operation and control of modern power plants system. A simulation based multi-experts evaluation method for HMI design of MCR was proposed. The functional simulation models of MCR HMI have been developed based on GL Studio. Modularization thinking was used to enhance the modeling efficiency. The evaluation indexes system of MCR HMI was determined, and the bottom evaluation indexes were extracted from the related ergonomic standards. Fuzzy theory was applied to integrate of evaluation comments of multi-experts in the multiexperts evaluation method. Finally, the evaluation software for MCR HMI was developed. The evaluation indexes system, evaluation method, and functional simulation models have been integrated into the software. The mentioned method is expected to enhance the HMI design quality of MCR of power plants.

Human-machine Interface (HMI) is critical for safety during automated driving, as it serves as the only media between the automated system and human users. To guarantee an understandable and transparent HMI, an evaluation method is urgently needed. However, there hasn't been a standardized and objective assessment method for HMI transparency. The methods used to evaluate HMI nowadays are primarily subjective and not efficient. To bridge the gap, an objective and standardized HMI assessment method was proposed in a previous study, but the adaptation to a simulator environment was not validated. Hence, the objective of this study is to first identify suitable objective workload measures in a driving context before incorporating them into the proposed transparency assessment method. In this study, two psychophysiological measures, electrocardiography (ECG) and electrodermal activity (EDA) were evaluated for their effectiveness in finding differences in mental workload among different HMI designs in a driving simulator. Three HMI designs with different transparency were developed and used as independent variables. Besides the root mean square of successive differences (RMSSD) between normal heartbeats from the ECG and the skin conductance response (SCR) from the EDA, self-reported NASA-TLX scores were also evaluated and considered as dependent variables. The study was conducted in a static driving simulator with a field of view of 120 degrees. A total of 24 participants were recruited, and each experienced 12 trials counterbalanced for HMI designs and driving scenarios. Participants were asked to monitor the HMI constantly and activate SAE Level 2 automated driving system whenever they felt comfortable. During the interaction, the eye tracker was applied to identify the time points when participants were gazing at the HMI designs. These time points were later used as references to calculate the corresponding RMSSD and SCR. Results showed that the RMSSD from ECG and the SCR from EDA were able to identify significant differences in objective mental workload when interacting with in-vehicle HMIs. Plus, the same correlations among HMI designs for two psychophysiological measures and the NASA-TLX were also identified. To the best of our knowledge, this study is the first to use psychophysiological measures to estimate the mental workload when interacting with HMI during automated driving. The results of this study could be used as a firm ground for future research. The findings not only help identify suitable objective workload measures for the interaction with HMI during simulator driving but also serve as the first step toward a standardized transparency assessment method.

Development and evaluation of a human machine interface to support mode awareness in different automated driving modes

In order to provide more convenient options for users and developers, the design of Human Machine Interface (HMI) based on ARM and embedded Linux is put forward. It makes full use of multiple peripherals of ARM and flexibility of Linux OS. Firstly, hardware design of the HMI system is presented. Then methods of embedded Linux transplanting and the device drivers programming are discussed. Finally, running results and applications of the designed HMI are considered. The design combines the features of traditional HMI and Micro Control Unit (MCU) HMI, including low cost, rich interfaces and easy programming.

For achieving higher level safety in aviation, it is strongly required to reduce accidents involving human factors. Actualizing appropriate human-machine interface (HMI) design is a key issue for preventing significant hazards resulted from human errors. In the present study, as an evaluation method for HMI, a human-machine system simulation called Pilot Cognitive Simulator (PCS) has been developed. The main purpose of the PCS is achieving qualitative evaluation of HMI design from the aspect of information contents thorough analysis of interaction between pilots' cognitive process and HMI in simulation environment. In an experimental simulation-based evaluation of a prototype information display, PCS could successfully reveal the effectiveness and the possible adverse effect of the supporting display. These results are considered to demonstrate the basic effectiveness of PCS as a supporting tool for achieving more reliable HMI design

Cooperative driving in a Connected Vehicle (CV) environment has received increasing attention over the years due to its ability to enhance driving safety and efficiency. For a cooperative driving task that requires speed adaptation, the recommended speed is displayed through human-machine interface (HMI). The design of HMI is expected to affect drivers' compliance and understanding of recommended speed and thus impact the driving performance. However, the effects of HMI design on cooperative driving performance are yet to be explored. In this study, three HMIs were designed: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δv$</tex-math></inline-formula> HMI (baseline, displays the speed difference between optimal and current driving speed), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δt$</tex-math></inline-formula> HMI (displays the time difference between optimal and estimated arrival time), and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δv$</tex-math></inline-formula> -graphic HMI (displays the speed difference using a variable graphic form). The HMI designs follow the skills, rules, and knowledge (SRK) taxonomy. To test the effects of the HMI design on cooperative driving performance, we developed a multi-driver driving co-simulation platform, which can simulate a cooperative driving environment and thus verify the HMI design. Driving simulator experiment shows that the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δt$</tex-math></inline-formula> HMI deteriorated the speed adaptation accuracy, while the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δv$</tex-math></inline-formula> -graphic HMI improved the driving performance. The questionnaire data revealed that the participants preferred the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Δv$</tex-math></inline-formula> -graphicHMI,as itwashighly rated in termsofsystemusability and user experience. The findings of this study provide insightsfor the HMI design for cooperative driving applications.

Evaluation of hydraulic excavator Human–Machine Interface concepts using NASA TLX

This study investigates the influence of human-machine interface (HMI) design on passenger trust in autonomous electric vertical take-off and landing (eVTOL) vehicles. An immersive simulator-based experiment was conducted with 34 participants, exposing them to four HMI conditions: baseline, movement, hazard detection, and full information condition. As related measures of passenger trust, we collected self-reported measures including trust, perceived safety, perceived reliability, and intention to use. In addition, physiological measures including gaze behavior, electrodermal activity, and heart rate were collected. The results indicated that movement and hazard detection information improved passenger trust, suggesting that HMI design could play a crucial role in enhancing the acceptance of autonomous eVTOLs. In addition, gaze behavior showed a stronger relationship with self-reported trust than other physiological measures. The findings underscore the importance of HMI design in fostering passenger trust, which is critical to the success of urban air mobility.