Hiroshi Furukawa

A flexible delegation-type interface enhances system performance in human supervision of multiple robots: empirical studies with RoboFlag

Three experiments and a computational analysis were conducted to investigate the effects of a delegation-type interface on human supervision of simulated multiple unmanned vehicles. Participants supervised up to eight robots using automated behaviors (plays), manual (waypoint) control, or both to capture the flag of an opponent with an equal number of robots, using a simple form of a delegation-type interface, Playbook. Experiment 1 showed that the delegation interface increased mission success rate and reduced mission completion time when the opponent posture was unpredictably offensive or defensive. Experiment 2 showed that performance was superior when operators could flexibly use both automated behaviors and manual control, although there was a small increase in subjective workload. Experiment 3 investigated additional dimensions of flexibility by comparing delegation interfaces to restricted interfaces. Eight interfaces were tested, varying in the level of abstraction at which robot behavior could be tasked and the level of aggregation (single or multiple robots) to which plays could be assigned. Performance was superior with flexible interfaces for four robots, but this benefit was eliminated when eight robots had to be supervised. Finally, a computational analysis using task-network modeling and Monte Carlo simulation gave results that closely paralleled the empirical data on changes in workload across interface type. The results provide initial empirical evidence for the efficacy of delegation-type interfaces in human supervision of a team of multiple autonomous robots.

Supporting System-Centered View of Operators Through Ecological Interface Design: Two Experiments on Human-Centered Automation

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 from 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.

A systematic method for rational definition of plant diagnostic symptoms by self-organizing neural networks

Abstract A method for evaluation of feature representations and definition of appropriate symptoms for diagnosis of large-scale artifacts is proposed in this paper. The central idea is the extraction of diagnostic information in symptoms obtained by a feature representation through automated categorization. Each possible feature representation is regarded as a feature vector in a specific parameter space. The Kohonen self-organizing network technique was applied to the feature vectors in order to obtain the optimal number of categories. Useful evaluation measures for the rational definition of symptoms were derived from the results of the categorization. By using these measures in evaluation processes, an appropriate set of feature representations can be implemented in a diagnosis system. The performance of the proposed method was evaluated through numerical experiments with a nuclear power plant simulator.

Computer simulation for the design of authority in the adaptive cruise control systems under possibility of driver's over-trust in automation

It is often said that humans must be maintained as the final authority over automation. However, that does not necessarily mean that human must be maintained as the final authority at all times and on every occasion. Design of authority is crucial for automobile, especially when there is possibility that the driver becomes complacent by trusting the automation excessively and when available time for safety control or information for situation understanding is limited. This paper gives a computer simulation method for analyzing the complacency effect and for investigating the efficacy of the trading of authority, by taking as an example the design of safety control schemes for driving with the adaptive cruise control systems.

Mode awareness of a dual-mode adaptive cruise control system

This paper presents results of an experimental study on mode awareness in an adaptive cruise control system with two operational modes. Two cognitive experiments were conducted using a low-fidelity driving simulator. First, the understandability of the system behaviors was investigated in a situation in which the system lost sight of a target vehicle. The simulated driving under suppression on the system state information shows that some participants exhibited difficulty in predicting the system behavior in complicated situations. Through an analysis of participants behaviors and understanding, valuable information that may improve their mode awareness was identified. The second experiment examined and compared design alternatives for the activatable and operational speed ranges in terms of the convenience and understandability. The results suggest that it may be possible to emphasize the convenience in the use of the ACC system without leading greater confusions in drivers mode awareness.

Operator's situation awareness under different levels of automation; evaluations through probabilistic human cognitive simulations

The human-centered automation concept claims two general requirements on situation awareness (SA) of human operators. One is the necessity of keeping the SA of an artifact, and the other is keeping the SA of automation. Nevertheless, the fundamental methods or techniques, especially quantitative ones, are not mature enough to be used as rational tools for human-machine design. An important approach for establishing the method must be identification of a proper level of automation, where ten levels are proposed by T.B. Sheridan (1999). A goal of the research presented is to establish a theoretical framework for evaluating automation levels from a viewpoint of operators situation awareness in real domains. A method using discrete event simulation is developed, and applied to a particular artifact: a nuclear power plant.

Situation-adaptive interface based on abstraction hierarchies with an updating mechanism for maintaining situation awareness of plant operators

Maintaining the situation awareness of human operators is one of the essential issues concerning the human-centered automation concept. There are two general requirements derived from the concept: (1) human operators must be kept adequately informed, and (2) the operators must be able to monitor the automation which is assisting them. This paper describes sub-requirements for human-machine interfaces to achieve these requirements. They are revealed through a theoretical analysis with following viewpoints: functions, means and ends, intentions, the reforming of models, and unanticipated situations. Along with these results, a design concept (a situation-adaptive interface based on dynamic abstraction hierarchies) is proposed.

A pedestrian navigation method for user's safe and easy wayfinding

In recent years, most of mobile phones have a function of pedestrian navigation guidance. It was reported that users sometimes feel anxiety because of low accuracy of the position estimation especially in urban area and delay of information updating. In order to reduce the anxiety, a route planning algorithm is proposed in this study, which weighs users difficulty (or easiness) of locating own current position as well as total physical distance of courses. The difficulty is estimated by valuation functions based on the recognizability and visibility of landmarks. An experimental study conducted in real situation using a prototype system to examine and refine the model for the optimal route planning. As the result, a modified model is proposed as a promising method of route planning for users easy wayfinding.

A Quantitative Evaluation Method of Landmark Effectiveness for Pedestrian Navigation

In recent years, most of mobile phones have a function of pedestrian navigation guidance. Even though performance of the function has been improved with Global Positioning System (GPS) and high information and communication technologies, it was reported that users sometimes feel anxiety because of low accuracy of the position estimation especially in urban area and delay of information updating. The purpose of our work is to propose pedestrian navigation method to reduce anxiety of users. We propose evaluation functions to estimate various landmarks effectiveness based on the recognizability, and visibility, and a route planning algorism for safe and easy way finding. The estimation model was constructed through several cognitive experiments about recognizability and visibility for different types of landmarks.

An Empirical Study on Ecological Interface Design for Multiple Robot Operations: Feasibility, Efficacy, and Issues

Multiple robots systems are one of effective solutions to implement robust, flexible, and adaptable systems that can be used in various conditions (Lee et al., 2000). The systems are increasingly being used in environments that are inaccessible or dangerous to humans (Stoeter et al., 2002 ; Chaimowicz et al, 2005). Operations in these environments are numerous, and include reconnaissance, exploration, and surveillance. As an example, one of promising areas of the application is a network robots system, which is a distributed architecture for remote control of multiple robots systems (Wirz et al., 2006). Another example is swarms of insect robots (Lee et al., 2000). Large amount of small and simple robots are used to achieve tasks in a form of agent-based automation. Regardless of their purpose of use, there are several factors which pose a challenging problem in supervision and management of multiple robots. The operators task involves not only manipulation of each robot but also achievement of the top goal that has been assigned to the entire team of humans and robots. Clearly, support of the operator’s skill-based behaviours is important. Equally, it is important to support human operators in their understanding of the overall state of a work-in-progress and the situation around it using a system-centred view. Although cognitive resources of humans are limited, operators are demanded to understand highly complex states and make appropriate decisions in dynamic environment. Furthermore, human-machine interfaces (HMIs) can display large amounts of complex information which risk overwhelming the operator at exactly the worst time, i.e., in an emergency situation (Sheridan, 2000). As a consequence, there has been increased interest in developing human-robot interfaces (HRIs) for human supervision of multiple robots (Goodrich et al., 2005). The main goal of our research project is the development of an interface design concept based on ecological interface design (EID) for human supervision of a robot team. EID is a design paradigm based on visualization of constraints in work environment onto the interface to reduce the cognitive workload during state comprehension (Vicente, 1999; Vicente & Rasmussen, 1992; Vicente, 2002). EID provides information about states of functions that are necessary to achieve the top goal of a human-machine system. Information on function is identified using the abstraction-decomposition space (ADS) (Rasmussen, 1986). An ADS is a framework for representing the functional structures of O pe n A cc es s D at ab as e w w w .in te hw eb .c om