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Raubal Martin

Structuring Wayfinding Tasks with Image Schemata (Diploma Thesis)

Wayfinding is a basic activity that people do throughout their entire lives as they navigate from one place to another. Many theories of spatial cognition have been developed to account for this behavior. But most of the computational models focus on knowledge representation (e.g., cognitive maps) and do not consider the process of structuring wayfinding tasks and space. This thesis presents a methodology based on image schemata to structure people's wayfinding tasks. Image schemata are recurring mental patterns (e.g., the CONTAINER or PATH schema) that people use to understand a spatial situation. They are highly structured and grounded in people's experience.

The area of our attention is airport space which is used as a case study. Many airports are badly designed and passengers are often unfamiliar with the particulars of the situations. We compare two selected airports in regard to the ease of performing a common wayfinding task. In order to do so, the methodology of structuring space with image schemata is combined with a proposed wayfinding model. We show that sequences of image schemata are sufficient to describe wayfinding tasks in spatial environments at an abstract level. Therefore, they can be used to compare the complexity of wayfinding tasks for different airports.

The integration of image schemata into the design process of spatial environments such as airports (i.e., the implementation of our method in a computer system) will help to identify architectural problems with regard to wayfinding prior to construction. Our structuring methodology can be generalized and will, thereby, contribute to the design of future geographic information systems that are supposed to integrate elements of human spatial understanding.

Agent-based Simulation of Human Wayfinding: A Perceptual Model for Unfamiliar Buildings. (Ph.D. Thesis)

Researchers in the areas of human wayfinding, spatial cognition, computer science, and artificial intelligence have developed cognitively based computational models for wayfinding. These models focus primarily on learning a spatial environment and on the exploration of mental representations rather than the information needs for wayfinding. It is important to consider the information needs because people trying to find their ways in unfamiliar environments do not have a previously acquired mental representation but depend on external information. The fundamental tenet of this work is that all such information must be presented to the wayfinder at each decision point as knowledge in the world.

Simulating people’s wayfinding behavior in a cognitively plausible way requires the integration of structures for information perception and cognition in the underlying model. In this thesis we use a cognizing agent to simulate people’s wayfinding processes in an unfamiliar building. The agent-based model is grounded in the ontology and epistemology of the agent and its environment. Both are derived from human subjects testing using an ecological approach. This leads to two tiers in the conceptual model: simulated states of the environment and simulated beliefs of the agent. The agent is modeled with state, an observation schema, wayfinding strategies, and commonsense knowledge. The wayfinding environment is modeled as a graph, where nodes represent decision points and edges represent lines of movement.

The perceptual wayfinding model integrates the agent and its environment within a Sense-Plan-Act framework. It focuses on knowledge in the world to explain actions of the agent while performing a wayfinding task. We use the concepts of affordance and information to describe what kinds of knowledge the agent derives from the world by means of visual perception. Affordances are possibilities for action with reference to the agent. Information such as from signs is necessary for the agent to decide which affordances to utilize. During the navigation process the agent accumulates beliefs about the environment by observing task-relevant affordances and information at decision points. The utilization of a so-called “go-to” affordance, i.e., following a pathway, leads the agent from one node to another where it is again provided with percepts. A successful navigation corresponds to the agent’s traversal from a start to a goal node. The perceptual wayfinding model concentrates on the actual information needs during wayfinding and does not focus on learning a spatial environment.

The proposed formal algebraic specifications of the agent-based model within a functional programming environment can be used to simulate people’s wayfinding behavior in spatial information and design systems in a cognitively plausible way. The simulation helps to determine where and why people face wayfinding difficulties and what needs to be done to avoid them. We employ the specific case of wayfinding in an airport to demonstrate the perceptual wayfinding model. The result can be practically used to test the signage in the airport.


Human Wayfinding, Agent, Information, Affordances, Spatial Perception and Cognition, Algebraic Specifications, Simulation.

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