Rudy Darken

Department of Computer Science
Naval Postgaaduate School

1. Statement of Participation and Contribution

In the past three years, my work has taken on a new perspective that I originally did not anticipate. During the early stages of my dissertation research at The George Washington University, I discovered that, while virtual environments seem to be similar to real environments in many of the most obvious ways, I often became disoriented in VEs and had serious difficulties navigating in them. This caused me to question how the not-so-obvious differences between VEs and the real world were affecting my ability to navigate. This also made me wonder what other differences existed that would limit the effectiveness of VEs in general. The original focus was on determining principles that could be used to design navigable virtual spaces. This, of course, required some understanding of related fields outside of my own (I’m a computer scientist), such as cognitive psychology and geography. While I did not know it at the time, I was becoming involved in a much deeper subject; spatial cognition. While my interest has been, and continues to be, an understanding of spatial cognition as it applies to simulated spaces, the use of VEs has, in itself, presented opportunities for study I had not anticipated. Our current research agenda includes the study of navigation within VEs (e.g., How to build better VE applications through improved navigation.) as well as the study of VEs used as training aids for real world navigation tasks (e.g., How to use a VE to learn how to navigate real environments in general, or, how to use a VE to familiarize oneself with a particular real environment.).

What I bring to this workshop is a perspective from the computing sciences that is relatively uncommon. Most of my colleagues in my field do not have an interest in the use of technology in the study of humans and our relationship to our environment. In fact, most do not study humans at all in spite of the fact that all the technologies we deal with exist for the purpose of serving man. I contend that bridging the gap between "technologists" and "humanists" is essential to a better understanding of both people and the machines we use. Within the context of this workshop, a better understanding of how people navigate VEs may enable us to better understand how people navigate real spaces. Understanding how people navigate involves an understanding of cognitive models of spatial information -- oftentimes dynamic spatial information. From a practical standpoint, it is important to note that VEs allow manipulation of variables that cannot be manipulated in the real world. For example, we commonly vary environmental fidelity (e.g., remove objects or detail from objects) in ways that cannot be done to real spaces.

I have spent considerable time recently on trying to construct a better model of human navigation from what we have seen thus far. In particular, models that assume the navigability of the space (mostly man-made environments) seem to be easier to handle than more amorphous, or loosely structured spaces (such as natural environments). This is a topic I would like to discuss in this forum if possible.

2. Position Statement

In order for us to better understand how to solve navigation problems in virtual environments, it seems obvious that we need to understand more about how people navigate in the real world. In some ways, however, this point isn’t so obvious because VEs can be so vastly different from the real world that it could be argued that we’re talking about a different animal altogether. I disagree with this position in that people live in the real world, our navigation skills and strategies are born in the real world, and therefore if a VE does not leverage this real world foundation, then the task becomes so abstract that it cannot be performed at all. Consequently, we are keenly interested in how people acquire spatial knowledge and how that knowledge might be represented in memory for use in navigation tasks. While we often use VEs as a tool for study, our interests are in the general issues behind spatial cognition and how individual differences, environmental differences, and interactions with an environment affect navigation.

It seems apparent that individual differences play a major role in spatial knowledge acquisition. In addition to effects due to spatial abilities (e.g., mental rotation, visualization) which I will not discuss here, we have seen a great variety of strategies attempted in many of our environments. These strategies are clearly affected by past experience as well as the task and environment in question. There is a key element here that I have yet to see appear in a clear form in the literature. This has to do with confidence; confidence in one’s own skills and capabilities, and confidence in the available tools (e.g., maps, GPS, etc.). Individual differences in this one area are so vastly different that I can safely say that a large part of the variance we see in performance in some of our navigation tasks can be traced directly to confidence.

Case in point, a Marine with thirteen years experience in the field attempts an intermediate level sport orienteering course and succeeds in finding only one of nine targets in a full hour. For comparative purposes, in the same experiment, we had an Air Force Cadet with absolutely no field experience complete the entire course with time to spare. How can this be? Certainly the Marine is not such a poor navigator that he cannot do this task. In post trial interviews, we discovered that entering the task, he had a very high level of confidence in his ability to perform this task. He had some ballpark estimate as to how long he expected it to take to locate the first target, then the second, etc. As he made error upon error, and the time in which he expected to find the first target came and went, his confidence began to waver. Initially, he tried to place blame on the map. He commented on how the map was "wrong" or was missing important items. The monitor (an experienced Army Infantry officer) replied that he was absolutely certain that the map was correct. Later, the Marine began to question himself and his own abilities. There is no doubt that one officer performing very poorly on a task he should have been very good at in front of his peer also had an adverse effect. But as a person begins to question what he knows about a space and consequently, his ability to do the task at all, performance plummets. Why this happens and how it can be alleviated, possibly through familiarization in a VE, is a topic of interest to our group.

The next topic I want to touch on in this position statement has to do with the effect environment has on strategy and consequently, spatial knowledge acquisition. Being adept at navigation in one type of environment does not guarantee good performance in all types of environments. Yet, we have seen individuals who excel in navigation tasks no matter what the environment might look like (at least as compared to a group of individuals). This is true even when spatial abilities are not a factor. It is clear that some people approach navigation problems in a more coherent, environment independent fashion, while others learn the keys to success in one type of environment only. These differences can be highly sensitive. A number of world-class orienteers from the San Francisco Bay area orienteering club came down to Monterey to participate in our first study in natural environments. Some of them noted how their performance was not what it typically is in their own area because the vegetation in Ft. Ord (our testing area) is different from what they are used to. This had an adverse effect on their strategies. For example, some planned routes through coastal Chaparral (not a good idea) or were surprised at the height of some of the Oak forested areas. Others from that group were not affected at all. Their strategies did not depend on vegetation or richness of contour. Our interest here is in determining what makes an approach environment independent and determining if this is a trainable skill.

The last part of this has to do with the actual interface to the virtual environment. It is well known that spatial knowledge acquisition is affected by travel mode. That is, spatial information I attend to when on foot is different from when I’m on my bicycle, which is in turn different from when I drive my car, which is different from when I’m a passenger in a car. This topic becomes more confused when we introduce interfaces to VEs which often break all the rules of physical reality. The effects of interfaces on navigation are largely unknown. Unfortunately, most of the attention has been given to maneuverability issues of VE interfaces. While it is important to be able to get from here to there, it is equally important (if not more so) to understand what "here" and "there" are and what the spatial relationships are between them. These, also, are affected by the interface, often adversely.

Most of this position statement has dealt with spatial knowledge acquisition. However, we are really interested in the bigger picture which also includes spatial knowledge representations and the use of this knowledge in navigation tasks. We have been trying recently to construct a model of spatial knowledge representations based on our work in natural environments. It is obvious to us that the flat landmark, route, survey knowledge (LRS) construct is oversimplified. There clearly is some hierarchical construct at work here. Attempts to use cluster analysis on route planning and execution in natural environments have thus far been unsuccessful. However, we believe that proximity between targets causes clustering to occur in some fashion resulting in high performance within a cluster and poorer performance between clusters. Thus far, we have not been able to show this consistently, at least to our satisfaction.

The last item I will discuss in this statement has to do with disambiguation of junctions. In orienteering, we refer to a "parallel error" as an error made when the orienteer thinks he is in one place that is spatially similar to where he actually is. This usually occurs at junctions. One of the reasons why problems occur with maps is that there often is no information by which to disambiguate two junctions. If we went there and looked at each junction, differences would appear, but they are not readily apparent from only the map. We think this is where a VE can be a useful tool. This actually falls more into the category of landmark knowledge than anything else. It has to do with recognizing a place correctly given whatever information is available. However, even in participants who perform our tasks very well, we do not yet understand how this disambiguation takes place. What do they encode and recall that works for them? Why do other fail where they succeed? Do both successful and unsuccessful participants recognize the junction as a unique place or does one or the other use it as part of a path between two other points? We believe that an understanding of this issue will lead us toward a more accurate model of human navigation and consequently, a better understanding of navigation in VEs.

3. Curriculum Vitae

Rudolph P. Darken, D.Sc.
Naval Postgraduate School
Department of Computer Science, Code CS/Dr
Monterey, California 93943-5118
(408) 656-4072, (408) 656-4083 (fax)

Research Experience

Naval Postgraduate School, Department of Computer Science 1996 - present. Assistant Professor of Computer Science. Tenure track.

Naval Research Laboratory, Tactical Electronic Warfare Division 1991 - 1996. Director of the TEWD Virtual Environment Laboratory.


The George Washington University
D.Sc. Computer Science October 1995. Advisor: John Sibert. Topic: Wayfinding in Large-Scale Virtual Worlds. Minor areas of study in Psychology (Human Factors) and Artificial Intelligence

M.S. Computer Science May 1993. Advisor: John Sibert. Topic: Navigation and Orientation in Virtual Space.

Selected Publications

  1. Darken, R.P., Allard, T., & Achille, L. (1998). Spatial Orientation and Wayfinding in Large-Scale Virtual Spaces: An Introduction. Presence: Teleoperators and Virtual Environments, 7(2), pp. 101 - 107.
  2. Darken, R.P., & Sibert, J.L. (1996). Navigating in Large Virtual Worlds. The International Journal of Human-Computer Interaction, 8(1), pp. 49 - 72.
  3. Sullivan, J., Darken, R., & McLean, T. (1998). Terrain Navigation Training for Helicopter Pilots Using a Virtual Environment. Third Annual Symposium on Situational Awareness in the Tactical Air Environment, June 2-3, 1998, Piney Point, MD.
  4. Goerger, S., Darken, R., Boyd, M., Gagnon, T., Liles, S., Sullivan, J., & Lawson, J. (1998). Spatial Knowledge Acquisition from Maps and Virtual Environments in Complex Architectural Spaces. Proceedings of the 16th Applied Behavioral Sciences Symposium, 22-23 April, U.S. Air Force Academy, Colorado Springs, CO. pp. 6 - 10.
  5. Darken, R.P. & Banker, W.P. (1998). Navigating in Natural Environments: A Virtual Environment Training Transfer Study. Proceedings of VRAIS ‘98, pp. 12 - 19.
  6. Darken, R.P., Cockayne, W.R., & Carmein, D. (1997). The Omni-Directional Treadmill: A Locomotion Device for Virtual Worlds. Proceedings of UIST ‘97, pp. 213 - 221.
  7. Darken, R.P., & Sibert, J.L. (1996). Wayfinding Strategies and Behaviors in Large Virtual Worlds. Proceedings of ACM SIGCHI 96, pp. 142 - 149. (See also CHI 96 Conference video).
  8. Darken, R.P., & Sibert, J.L. (1993). A Toolset for Navigation in Virtual Environments. Proceedings of UIST ‘93. 157 - 165.

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