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Supporting System-Centered View of Operators Through Ecological Interface Design: Two Experiments on Human-Centered Automation Hiroshi Furukawa and Raja Parasuraman Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2003 47: 567 DOI: 10.1177/154193120304700366

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SUPPORTING SYSTEM-CENTERED VIEW OF OPERATORS THROUGH ECOLOGICAL INTERFACE DESIGN: TWO EXPERIMENTS ON HUMAN-CENTERED AUTOMATION

Hiroshi Furukawa Raja Parasuraman University of Tsukuba The Catholic University of America Tsukuba, Japan Washington DC, USA The Catholic University of America Washington DC, USA

Human operators faced with an unexpected situation while controlling a complex system can take effective action if they are provided a system-centered view based on Ecological Interface Design (EID). To date there is only limited empirical support for the efficacy of EID in enhancing human-automation interaction. This paper presents results from two studies of EID in human-automation interaction, drawn fiom different domains, flight simulation and process control. In Experiment 1, use of an integrated display with an emergent perceptual feature was found to eliminate the automation complacency effect in monitoring for engine system malfunctions during a flight simulation task. In Experiment 2, a display with a multi-level representation of the intention of the automated controllers in a process control system was found to improve human-automation collaboration. These studies show that explicit visualization of the functional structure of a human-automation system in the interface supports the system-centered view in operators, thereby enhancing system performance.

INTRODUCTION accomplish predefrned tasks. In this analysis, situations and the corresponding procedures are predefined, so that The concept of human-centered automation proposes that information can be selected efficiently, and HMI design is humans remain in command over automated sub-systems arranged to support operators appropriately in those situations. because they bear the ultimate responsibility for safety, However, this specificity may not promote comprehension of especially in situations that the automation cannot handle states by operators in unanticipated situations. (Billings, 1997, Sheridan, 2002). Humans can and do take System-centered work analysis shows the functional prompt measures under such circumstances, but only if they structure of work in the system. The analysis is based on the comprehend the state of the system and have sufficient time Abstraction-Decomposition Space (ADS) concept proposed by (Endsley, 1995). The time necessary for human operators Rasmussen (1986), which is also known as the Abstraction includes (at least) the time for detecting failures in the Hierarchy. ADS is a hierarchical representation of relations automated controllers, comprehending the system states, and between a top goal and physical components with multiple making decisions and planning actions. A technology-centered viewpoints, such as abstraction and aggregation. In this approach to the design of automation, however, typically fails analysis, the HMI is designed to support operators to have a to cover unanticipated situations, and ignores the importance system-centered view. A design concept based on the ADS is of supporting correct comprehension of system states and Ecological Interface Design (EID) (Vicente and Rasmussen, behaviors by human operators (Parasuraman and Riley, 1997; 1990, 1992), in which the ADS of a target system, i.e., the Parasuraman, Sheridan, and Wickens, 2000). means-end relations of the work, is represented to allow How can the human-centered automation concept be operators to comprehend the ADS intuitively. This can be implemented to foster greater system comprehension? Human thought of as the externalization of the operator's mental operators have some limitations in understanding complex model of the system onto the HMI (Rasmussen and Pejtersen, system states. Automation is typically fast and precise and can 1995). The HMI is also designed to support skill-, rule- and display large amounts of complex information, which can knowledge-based behaviors (Rasmussen, 1986). overwhelm the operator at exactly the worst time, i.e., in an Vicente (2002) proposed the need for additional empirical emergency condition. Furthermore, if operators exhibit studies to examine the effectiveness of the EID concept. This over-reliance on automation, they may take more time to paper presents results from two experiments drawn from detect system malfimctions than without automation different domains, flight simulation and process control, which (Parasuraman, Molloy, and Singh, 1993). Thus, the examined EID in human-automation interaction. Experiment 1 human-machine interface (HMI) must support operators to investigated the effects of an integrated display on monitoring allow better comprehension of system and automation states. for engine malfunctions in a flight simulation task. Experiment HMI design can be informed by task analysis, of which 2 examined the effects of multi-level representation of two major types are task-centered and system-centered work intention of automated controllers based on ADS in a process analysis (Miller and Vicente, 200 1). Task-centered analysis control task. shows the tasks that can be or should be done for work involving a given system in a particular situation. An assumption of the analysis technique is that the operator is responsible for performing the actions necessary to

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EXPERIMENT 1

The tasks of the operators in this study were the detection of failures and state comprehension in a simulation of an aviation environment. Cockpit automation has been a fertile area for investigation of human-automation coordination problems (Billlings, 1997; Parasuraman and Byme, 2003; Sarter, Billings, and Woods, 1997). One of the problems that has been investigated is pilot over-reliance on automation designed to monitor the status of aircraft. systems, so that when occasional failures occur, they are less likely to detect the failure (or NORMAL WARNING FAULT slowed in responding) compared to when they perform the task manually (Parasuraman et al., 1993). This automation Figure 1: The integrated display based on the EMACS. complacency effect reflects an allocation policy away fiom the automated task to the other tasks that the operator has Results to perform simultaneously (Moray and Inagaki, 2000; Parasuraman et al., 1993). Hence, one way to reduce the effect There were no differences in pilot performance on the would be to use an integrated display based on EID principles engine-systems task between the integrated and non-integrated to display the engine system state, both under normal display conditions when there were no failures in automation conditions and when malfunctions occur. control. This indicates that interfaces based on EID do not The experiment tested the hypothesis that the visual necessarily incur a performance cost under routine, normal attentional demands of monitoring an integrated display would conditions. When the automation failed to detect and be reduced compared to a non-integrated display (Bennett and diagnose malfunctions, however, pilot monitoring Flach, 1992). The design was similar to that of Molloy and performance (detection and diagnosis rates) was significantly Parasuraman (1994), except that eye movements were better for the integrated EMACS display than for the standard, recorded in order to evaluate the attention allocation strategies non-integrated EICAS display (p<.O 1). Moreover the and that pilots instead of students were used as participants. automation complacency effect -- the reduction in performance for automated compared to manual monitoring -- Method was eliminated with the integrated display. As Figure 2 shows, there was a significant reduction in the system malfunction 12 general aviation pilots aged 23-35 years performed the rate between manual and automation control for the Multi-Attribute Task (MAT) involving the following non-integrated display (p<.OO 1). For the integrated display, sub-tasks: a manual, two-dimensional compensatory tracking however, the detection rate was relatively high and was not task, a manual resource management task requiring balancing significantly different between the two modes of control. of the fuel tanks of the aircraft, and an automated engine-systems-failure detection task. The interface used to Cost of Automation display the engine-systems task in the MAT was changed and Complacency Eliminated consisted either of an integrated or a non-integrated display. e- The pilot's monitoring task was to detect deviations in 2" different engine parameters (EPR, N1, EGT, etc) and take z appropriate corrective actions. The integrated display was MANUAL based on the Engine Monitoring and Crew Alerting System 'O ALITOMATELI (EMACS), which was displayed with a deviation bar graph Dc) 20 1). (see Figure The tips of the four bars displayed an emergent 0 perceptual feature--an invisible line when the state of engine EICAS EMACS was normal--which provided a ready indication of system (Non-Integrated) (Integrated) normality or malfunction without the expenditure of much attentional effort. The line indicated abstract information Figure 2: System malfunction detection rate for the obtained by the state parameters, which is nomality ofthe non-integrated and integrated displays. engines. If one of the engines failed, the emergent line was distorted, and so pilots could detect it quite easily. The Analysis of eye movements indicated that there were no non-integrated display was based on a traditional Engine significant differences in the number of fixations of the Indicator and Crew Alerting System (EICAS), which was engine-systems task between display types. However, displayed with circular gauges showing engine parameters fixation "dwell" times were significantly shorter with the separately in an analog display. EMACS than with the EICAS display (pC.01).

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Discussion had been experienced before as well as unexpected events. During a brief interview after each scenario, participants were These findings indicate that automation complacency asked to tell about indicated parameters, information, rules, results from an attention allocation policy away from the and other knowledge used in the state comprehension. The use automated task to the other manual tasks that the operator has of these information parameters was verified based on fixation to perform (Parasuraman et al., 1993). As a result, if position data collected by eye-movement recording. abnormalities in the automated control of a task occur, malhnctions may not be correctly detected and diagnosed. However, if these are shown to the operator using an

integrated display based on EID, fewer attentional resources I are needed to detect and diagnose the malhnction. This was supported by the eye movement analysis: pilots had shorter visual fixations ("dwells") with the EMACS display, yet they performed better than with the EICAS display, suggesting that display integration facilitated efficient information extraction. Also, EID eliminated the automation complacency effect. W

EXPERIMENT 2

The objective of this experiment was investigation on human-automation interaction supported by an ADS-based display with intention of automated controllers in a process control system. Figure 3: A target system: a heated water %pply plant.

Materials

This study used a heated water supply plant (Figure 3), which was a simplified version of the DURESS process control simulation (Vicente and Rasmussen, 1990). There were two automated controllers for each line. A controller A-H used a heater to adjust temperatures of water to demand values. A controller A-V for an inlet valve had three different modes, which was hard for participants to recognize (Furukawa and (a) Level mode. Inagaki, 2001). The EID fiamework was used to support operators in their ability to prevent conflicts with the automated controllers by explicitly representing the intentions (i.e., goals and means) of the automation on the HMI (Furukawa and Inagaki, 2001). Two types of the center part of the HMI are described in Figure 4, which are for Level mode and for Temp mode. These forms were automatically changed according to the mode. Dotted lines in the Level mode represent a goal state of the automated systems, where A-H tried to keep the temperature (b) Temp mode. at the demand value, and A-V tried to keep the level. In Temp Figure 4: The representation forms for intention of the mode, the intention ofA-V to adjust the temperature to a automated controllers in different modes. demand was indicated. Results Method The data collected by interviews and eye-movement Participants were 16 university students who performed the recording showed that the participants could be categorized simulation with the intention-represented EID and with a into three groups based on their control strategies (Table 1). standard EID display (Furukawa, Nakatani and Inagaki, 2002). Local-goal-controllers were those who controlled only The order of using the HMI was counterbalanced across the responsible tasks as one of controllers and completely left participants. After participants were allowed to see one of the some tasks to the highly capable automated controllers. The displays for 8-10 seconds, they were asked to report key second and third groups held themselves responsible for all parameters in the current state of the system as well as its tasks including tasks controlled by the automation. hture state, the control operations to be taken, and the target Supervisors supervised the automated controllers and states of the operations. The scenarios included situations that intervened in the tasks at some situations, and

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Power-controllers controlled all tasks as if they were the only and (3) all supervisors could take appropriate actions to trustable controller. All Supervisors used the information cooperate with the controllers without any conflicts when they about intentions of the automated controllers, but none of the used the intention-represented EID, but some failed without it. Local-goal-controllers or Power-controllers did (Table 2). The importance of the information about intention of the The performance in the state comprehension test of automated controllers heavily depended on the strategies that Supervisors was significantly higher than that of Local-goal- the participants used. Some participants failed to supervise controllers (F(1,26) =13.73; p<.OOl, Figure 5). particular tasks performed by automated controllers, perhaps Some conflicts between participants and automated because they thought that the controllers had complete controllers were observed in a particular scenario, reflecting responsibility for the tasks. The intention information misunderstanding by participants on the intention of the indicated on the HMI was absolutely meaningless for them. controllers that were in a different mode than usual (Table 2). Some of the Supervisors made the conflicts when they used GENERAL DISCUSSION the standard EID, but none with the intention-represented EID. Under routine operating conditions that have been Table 1: The groups based on the observed control strategies. experienced many times before, human operators can Strategies The number of participants effectively monitor and control a complex system designed Supervisors 10 according to a task-centered concept. Operators are trained to Local-goal-controllers 4 achieve their tasks in accordance with procedures prepared by Power-controllers 2 the system designers. The HMI is designed accordingly to support operators in their following of procedures. While this design concept is efficient for normal operations, it may not be Table 2: The number of participants used the intention appropriate for abnormal or unanticipated conditions. In these information, and engaged conflicts with the automated circumstances, a system-centered view is necessary for controller using the two types of EID. operators to control a system efficiently, comprehend system - _. Conflict state, make operational plans, and execute the plans. EID can Strategies Intention info. Standard Intention- provide operators with a system-centered view for operations EID represented under such conditions, as supported by the empirical evidence Supervisors 101 10 21 10 01 10 provided from two domains, flight simulation and process Local-goal-controllers 0 / 4 1 /4 2/4 control. Power-controllers Of2 012 012 The first study provided empirical evidence in tasks of detection of failures and state comprehension in a flight simulation environment with automated fault management. Operators may take more time to detect failures and/or comprehend situations of tasks that are controlled by 1Mean+SD Mean-SD automation than by themselves when they have to conduct d- Mean other manual tasks simultaneously (Parasuraman et al., 1993). The reason may be that operators change their attention allocation policy, and attend less in the former situation than in the latter. Hence, any HMI that can reduce the attentional demands of information extraction and analysis should reduce or eliminate this problem. Visualizing implicit relations between significant parameters on HMI, which is one of the ;io' I key requirements in EID, has the ability to support operators r Supervisor Local-goal-cont. c to comprehend situations of tasks. The results of Experiment 1 Strategy showed that an integrated display eliminated the automation Figure 5: Performance in the state comprehension test in complacency effect and led to superior detection and diagnosis comparison of Supervisors and Local-goal-controllers. of engine malfunctions. These results are in agreement with the previous study by Discussion Molloy and Parasuraman (1994), who used the standard MAT task with students, but extend their findings to expert The results are indicative of the high potential of the participants (pilots) working with realistic engine monitoring intention-represented EID in supporting participants for systems (EICAS and EMACS). The present study also used appropriate state comprehension and decision making. This eye movement analysis, which showed that pilots made view is supported by three main findings: (1) all participants shorter "dwells" with the integrated EMACS display than with who took the supervising strategy explicitly used the intention the standard non-integrated EICAS display. This finding information; (2) the supervisors' performance in state shows that display integration facilitated efficient information comprehension and decision making was significantly higher extraction needed for malfunction detection and diagnosis. than that of non-supervisors who did not use the information;

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The second study provided empirical evidence for the 32-64. efficacy of the system-centered design concept in tasks of state Furukawa, H. and Inagaki, T. (2001). “A Graphical Interface comprehension and decision making in process control. When Design for Supporting Human-Machine Cooperation: automated controllers are mode-rich or have high capabilities, Representing Automation’s Intention by Means-Ends operators may fail to have a system-centered view, and devote Relations,“ Proc. of 8th IFAC/IFIP/IFORS/IED Symposium their own cognitive resources to some particular tasks to on Analysis, Design, and Evaluation of Human-Machine achieve the local goals, not the top goal of the entire system. Systems, pp. 65 1-656. One reason of the failure could be that operators are not Furukawa, H., Nakatani, H., and Inagaki, T. (2002). “Human- trained to have the system-centered view in controlling a machine interface for cooperation with automated systems target system. Extended training might eliminate the cause. based on awareness of goals and means,” Proc. ISOFIC Another reason of the failure could be that operators have 2002 International Symposium on the Future I&C for NPe difficulties acquiring an accurate mental model based on the pp.305-3 12. system-centered view, when the system is complicated and/or Miller, C. A. and Vicente, K. J. (2001). “Comparison of modes of the automated controllers are rich. Experiment 2 display requirements generated via hierarchical task and showed that visualizing the intention of the automated abstraction-decomposition space analysis techniques,” controllers on the HMI in the framework of ADS could International Journal of Cognitive Ergonomics, 5(3), effectively support operators to have appropriate mental 335-355. models of a target system and to comprehend states of the Molloy, R. and Parasuraman, R. (1994). “Automation-induced system with the system-centered view. To take appropriate monitoring inefficiency: The role of display integration actions to cooperate with the controllers without any conflicts, and redundant color coding.” In M. Mouloua, and R. rich mental models of the target system and automated Parasuraman (eds.), Human performance in automated controllers, which include their goals and means, were systems: Current research and trends, LEA, pp. 224-228. necessary. Moray, N. and Inagaki, T. (2000). “Attention and complacency,” Theoretical Issues in Ergonomics Science, CONCLUSIONS 1, 354-365. Parasuraman, R. and Byrne, E. A. (2003) “Automation and These studies show that the system-centered view is usefbl human performance in aviation,” in P. Tsang and M. for appropriate state comprehension and decision making in Vidulich (eds.) Principles of Aviation , Mahwah, human-automation interaction, and that HMIs based on EID NJ: Erlbaum, pp. 3 11-356. can support operators to have the system-centered view. Parasuraman, R. and Riley, V. (1997). “Humans and Empirical evidence for the efficacy of the EID approach to automation: use, misuse, disuse, abuse,” Human Factors, HMI design was shown in two experiments in different 39(2), 230-253. domains, flight simulation and process control. However, Parasuraman, R., Molloy, R., and Singh, I. L. (1993). empirical evidence of the effectiveness of this approach, while “Performance consequences of automation-induced necessary, is not sufficient. In addition, the EID approach “complacency”,” International Journal of Aviation needs to be applied to actual systems. Currently, the Psychology, 3, 1-23. techniques for designing EID-based HMIs are not mature Parasuraman, R., Sheridan, T., and Wickens, C. (2000). “A enough to be fully applied to real domains. 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