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People often get lost in buildings, including but not limited to libraries, hospitals, conference centers, and shopping malls. There are at least three contributing factors: the spatial structure of the building, the cognitive maps that users construct as they navigate, and the strategies and spatial abilities of the building users. The goal of this article is to discuss recent research on each of these factors and to argue for an integrative framework that encompasses these factors and their intersections, focusing on the correspondence between the building and the cognitive map, the completeness of the cognitive map as a function of the strategies and individual abilities of the users, the compatibility between the building and the strategies and individual abilities of the users, and complexity that emerges from the intersection of all three factors. We end with an illustrative analysis in which we apply this integrative framework to difficulty in way-finding.

Signage systems are critical for communicating spatial information during wayfinding among a plethora of noise in the environment. A proper signage system can improve wayfinding performance and user experience by reducing the perceived complexity of the environment. However, previous models of sign-based wayfinding do not incorporate realistic noise or quantify the reduction in perceived complexity from the use of signage. Drawing upon concepts from information theory, we propose and validate a new agent-signage interaction model that quantifies available wayfinding information from signs for wayfinding. We conducted two online crowd-sourcing experiments to compute the distribution of a sign's visibility and an agent's decision-making confidence as a function of observation angle and viewing distance. We then validated this model using a virtual reality (VR) experiment with trajectories from human participants. The crowd-sourcing experiments provided a distribution of decision-making entropy (conditioned on visibility) that can be applied to any sign/environment. From the VR experiment, a training dataset of 30 trajectories was used to refine our model, and the remaining test dataset of 10 trajectories was compared with agent behavior using dynamic time warping (DTW) distance. The results revealed a reduction of 38.76% in DTW distance between the average trajectories before and after refinement. Our refined agentsignage interaction model provides realistic predictions of human wayfinding behavior using signs. These findings represent a first step towards modeling human wayfinding behavior in complex real environments in a manner that can incorporate several additional random variables (e.g., environment layout). Keywords Cognitive agent • Information theory • Entropy • Artificial intelligence • Agent-based model • Signage system Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper is in two sections, the first section presents a review of recent research in the areas of neuroscience, cognitive science and architecture with particular respect to what is currently understood about how buildingusers find their way around complex buildings. It goes on to define four areas of promising, potential future research located on the boundaries between these three disciplines, these being: spatial knowledge acquisition, orientation, multilevel environments and environment intelligibility. In the second half of the paper, it suggests how such current research and/or any future program of research could be used to aid architects in the design of new buildings. One such method suggested is the creation of designguidelines or heuristics based upon research into navigation and wayfinding. The paper concludes with an example list of eight sample guidelines.

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This study examined individual differences in spatial abilities of architecture students. Students at different educational levels were assessed on spatial ability tests that varied in their domain-specificity to architecture, with the hypothesis that larger differences between beginner and advanced students will emerge on more domain-specific tests. We also investigated gender differences in test performance and controlled for general reasoning ability across analyses. In a cross sectional study, master students (N = 91) outperformed beginners (N = 502) on two novel tests involving perspective taking and object composition, as well as on a standardized visualization of cross-sections test, but not on a standardized mental rotations test. Longitudinally (N = 117), spatial performance improved after the first bachelor year on visualization of cross-sections, object composition and mental rotation. Although both genders showed higher spatial test performance with increased experience, male students outperformed females across tests and levels of education. The results overall confirmed improvements in spatial performance during architecture studies, with partial support for the domain-specificity hypothesis. A gender gap among advanced students calls for further examining architecture-specific spatial thinking.

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