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Article Excerpt
INTRODUCTION
Although certain costs of adding automation to a machine or process are easy enough to anticipate (e.g., additional operator training), other costs have turned out to be much more subtle. Especially when operators are called upon to share control with an automation system, unexpected problems arise. These include bumpy transitions between automated and manual control (Meyel; Rubinstein, & Evans, 2001; Mosier, 2002) and automation surprises, which occur when the operator has a poor mental image of automation behavior or misses automation mode changes (Sarter, Woods, & Billings, 1997). The consequences arising from these unexpected problems can be dire, at times offsetting the improved precision and performance or reduced operator workload for which automation was added in the first place. Unraveling these costs and providing solutions has been the focus of much research in recent years.
A portion of the unexpected problems associated with sharing control between a human operator and an automation system can be attributed to the need for the operator to master two control interfaces and to learn two or more distinct operating modes. Whereas many machines present a manual control interface requiring continuous, direct control and certain manual skills, the typical automation interface presents a set of indicators, knobs, and buttons requiring intermittent input and certain analytical and decision-making skills (Mosier; 2002). When complex or unanticipated conditions arise, the traditional approach to "cooperation" is for the operator to interrupt the automation and take over full control through the manual interface (Christoffersen & Woods, 2002). When control is wrested away from the automation system, the advantages of automation (precision, computational speed, and other functions) are lost (Christoffersen & Woods, 2002). Bainbridge (1985) has noted that ironically, the manual skills of an operator who regularly gives up control to an automation system may begin to degrade from lack of practice, leaving him or her ill prepared to meet the heightened challenges that typically arise during automation failures.
What is needed is an intermediate, more collaborative mode of interaction. Ideally, the operator would be able to negotiate with and redirect the automation system without first disabling it and then restarting (Christoffersen & Woods, 2002). There would be a natural kind of "give and take" between the operator and the automation. In this paper, we propose an automation interface and associated control-sharing paradigm that does not include mode switching and therefore avoids the associated pitfalls. The operator needs to learn only one interface and one set of rules.
Another portion of the unexpected problems in automation can be attributed to the poor rate and quality of information transmission supported by most automation interfaces. In addition to the communication of current mode and action, efficient cooperation requires the communication of goal and intent. One approach to improving communication is the use of multimodal displays. Sarter (2002) has estimated the value of various modalities for guiding the operator's attention and effectively managing interruptions. To visual and auditory displays, Sarter (2002) has added haptic (kinesthetic and tactile) display, including vibrotactile cues on the manual control interface.
In automobile interfaces, both vibrotactile and pulse torque cues applied through a motorized steering wheel have been tested as a means of informing or warning automobile drivers (Driver & Spence, 2004; Schumann, Godthelp, & Hoekstra, 1992; Suzuki & Jansson, 2003). Beyond the use of haptics for discrete cues, haptic display has been used to automate vehicle steering in such a way that the driver can continuously monitor the automation actions (Switkes, Rossetter, Coe, & Gerdes, 2004). In this work, automation took the form of a virtual potential field to aid the driver in lane keeping. Any deviation from the center of a lane produced continuous haptic information about the automation's tendency to return the vehicle to the lane center.
In this paper, we also employ haptic display with the aim of enabling more effective negotiation and coordination of intent and actions. The promise of haptic display follows in part from its lack of overlap with the visual and auditory modalities, but further, haptic signals can be information rich in ways that are particular to the communication of intent, especially intent involving direction and magnitude. Further, we believe that signals encoded in force and motion are especially suited for informing the operator about automation intent because they can simultaneously convey intent and automation confidence in that intent. Mechanically mediated communication can even support negotiation of authority. For example, a particular motion imposed by the automation can be accompanied by larger reaction forces that resist motion inputs from the operator. Likewise, the operator could express his or her desire for increased authority by using high impedance or less "gave," possibly by cocontracting the muscles in his or her arm. This is the way two human operators would communicate if they both grasped the same manual control interface: Each operator would apply muscle action to extract his or her own desired response with a certain authority while simultaneously perceiving the other's intent and desire for authority by feel.
We propose, then, to combine the machine and automation interfaces into a single interface modeled after the traditional manual control interface. The human operator is presented only the standard manual interface, over which the automatic control system is also given authority. The automation system imposes its control effort through a motor coupled directly to the interface. The motorized manual interface becomes a haptic display, relaying information about the actions of the automation system to the human operator's haptic senses. In effect, we propose a return to the "contact" or "direct" mode of interaction, in which visual/kinesthetic perception and motor response are relied upon rather than the analytical and decision-making skills usually required by the automation system. In contrast to the use of vibrotactile cues for alert and display of discrete information, we use haptics to relay continuous signals to the operator. In our shared control scheme, the automation is placed in mechanical parallel with the operator and takes the form of an assist that actually intervenes in the control loop. The operator may choose either to yield to the assist while observing its action or to override it by exerting slightly more effort.
Through the motor on the interface, the automation may apply torques according to its own rules or control law, as a function of sensed machine state. For example, a steering wheel can be given a "home" position that is itself animated according to sensed vehicle position within a lane. The automatic controller can create virtual springs that attach the steering wheel to a moving home angular position that corresponds to the vehicle direction recommended by the automation. By feel, the operator can form a mental image of the springs attached to the moving home position, especially by haptically exploring the invariants of the reaction torque to his or her own input motions. To ensure that the automation can be overridden, it uses a limited mechanical impedance (essentially a limited stiffness).
The introduction of assist through a motor on a manual control interface has been studied extensively in the applications of haptic interface to teleoperated and virtual environments (Gillespie, 2004; Hayward, Astley, Cruz-Hernandez, Grant, & Robles-De-La-Torre, 2004). In these applications, assist is offered in the form of virtual fixtures that may be used by the operator as mechanical guides for controlling force or motion direction. Virtual fixtures have been shown to improve performance in targeting tasks (Dennerlein & Yang, 2001; Hasser, Goldenberg, Martin, & Rosenberg, 1998), peg-in-hole tasks (Payandeh & Stanisic, 2002; Rosenberg, 1993; Sayers & Paul, 1994), and surgical interventions (Park, Howe, & Torchiana, 2001). Virtual fixtures are usually fixed in the shared workspace; however, virtual fixtures composed of functions of time or recognized operator motions were studied by Li and Okamura (2005). In this work we also employ virtual fixtures, created by the automation in the workspace shared by the automation and operator. Our fixtures, however, are animated by the automation system. By and large, the focus in the field of haptic interface has been improved human/machine performance. The possible secondary benefits, such as reduced operator workload, have been overlooked in the literature.
The setting for our investigation of mechanically mediated control sharing is a driving simulator with a motorized steering wheel. Although our particular implementation is far removed from actual driving--our former setups were in fact closer (Steele & Gillespie, 2001)--we hope that our results may nevertheless contribute to ongoing work in the design of automation interfaces for driving. The primary goal in this paper is to quantify the primary and secondary benefits...
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