No abstract

Being the main user of any architectural product, the user's role in the designing process should be significant, especially in complex spatial spaces such as hospitals, museums, offices, and public-use buildings. This gives the users meta- roles such as communicators, performers, and interpreters. User-Centered Design (UCD) tries to optimize the fit of the spaces with how users can, want to, and need to use in these spaces, rather than forcing the users to change their behavior to accommodate the architectural spaces or designing dysfunctional spaces. Such spaces were designed neglecting the human factor and only using building regulations. The visitor’s parameters, profiles, spatial experiences, and the architectural configuration are what can affect the experience in architectural spaces. This paper explores a different UCD (user-centered design) approach in the evaluation of the built environment which is the parametric spatial analysis approach. The approach studies the spatial pattern of human behavior of a random selection of users, so it could represent any potential users in the buildings. Aiming to intensively engage users in the design process, the approach uses parametric spatial design in analyzing the visitor's behavior and deducing some design patterns and configurations that focus on different ways of user's engagement. This approach compares the definition of users, their roles, and the type of space envisioned and produced as well. This paper describes an approach that attempts to bridge the gap between parametric geometry modeling and methods for measuring the spatial properties of this geometry. In exhibition spaces with their different spatiality, visitors tend to have some indicators which can be measured. Accordingly, designers create functional spaces that suit the different types of visitors using parametric components that study the collective human behavior (organizational behavior). These functional spaces are designed through observation, user surveys, and interviews to simplify the complexity of decisions regarding the design process and visitor’s parameters, and to embed them into an algorithm that can solve the complexity of the visitor’s parameters. Analyzing visitors’ behavior and the spatial morphology improves the visiting experience and provides better interpretations. The analysis makes the designers aware of visitors’ circulation, visiting styles, behavior, patterns, tendencies, and trends within a wide diversity of spaces. Moreover, this analysis can be combined into an evolutionary algorithm to help solve problems.