Cognitive Modeling of Information Sources for Human Wayfinding under Uncertainty
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Date
2020-10
Publication Type
Doctoral Thesis
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Abstract
The growth in the global population and rapid urbanization has put tremendous stress on existing infrastructures. The increasing influx of people in built environments such as transportation hubs, hospitals, office and educational buildings, and shopping malls has become a cause of concern. The ability to maintain wellbeing and people's comfort in a densely populated, large, and complex building during a general circulation or disaster is an essential design issue. This issue is equally relevant when considering yet-to-be-built environments of the future. Architects, designers, and planners must rely on their expertise and intuition when accounting for how people navigate when designing spaces, which becomes prohibitive when accounting for the myriad of contexts that spaces must accommodate. A critical challenge towards managing and designing built environments is understanding (from a cognitive perspective, "User in Mind") how humans rely on various external indicators when navigating in these spaces.
Human wayfinding in a complex built environment is a dynamic process that is mentally demanding. It involves the acquisition, processing, and interpreting multiple wayfinding information sources in an environment and the head (i.e., spatial memory) to aid in route planning. These information sources include environmental landmarks, signage, spatial features, the presence and behavior of other people, and spatial memory of a familiar environment. These information sources are filled with uncertainty, often contradict one another, and are a dominating factor for individuals getting lost in complex environments. The ability for people to find their way is a critical function of built space and has far-reaching implications on the intended usage of a building, the quality of life of its inhabitants, and for security and disaster prevention.
This thesis attempts to model how humans acquire, perceive, and interpret information sources in their surroundings (e.g., signage, spatial features, crowd characteristics, and familiarity of the environment) when navigating in complex indoor environments. The main goal is to develop a cognitively grounded computational framework of human wayfinding, which models the uncertainty and fusion of multiple potentially conflicting information sources. The research can potentially have a transformative impact on our understanding of the cognitive underpinnings of human wayfinding, and enhance practices for architects, urban planners, and civil engineers, enabling real-time crowd management, disaster, and security applications as well as aid in the design of smart and connected environments.
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published
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Examiner : Sumner, Robert W.
Examiner : Hoelscher, Christoph
Examiner : Manocha, Dinesh
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ETH Zurich
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Subject
Cognitive Agent Modeling; Decision-Making under uncertainty; multivariate information fusion
Organisational unit
03987 - Hölscher, Christoph / Hölscher, Christoph