Fuzzy logic in agent-based modeling of user movement in urban space: Definition and application to a case study of a square

Abstract

The growing complexity of design processes increases the distance between designer and user which makes it challenging to consider user experience in design. Computational models can help us to simulate user behaviors where agents represent users as a collection of autonomous decision-making entities. In this context development of these models supports early stage decision-making in urban design. The aim of this study is to investigate how the user is involved in urban space and to analyze the relationship between urban space components and the users' movement to be able to develop a model for user movement simulation. This paper follows a five-step consecutive process: (1) data collection with observation studies and environmental analysis (2) interpretation of the data using fuzzy logic (3) agent-based model development (4) model implementation (5) evaluation and validation. The interpretation of the observation data is to calculate the attractiveness value of urban space components with fuzzy logic. The value is then defined as attract force on agent-based simulation model. The simulation results are evaluated comparatively using observation outputs. As a case study for the model capabilities demonstration a square is chosen (Konak Square Izmir Turkey). Two models for morning and evening timelines are defined and tested to be able to simulate user movement in the square. Thereafter the efficiency of the model is examined by comparing the simulation results and observation data by the Mean Absolute Percentage Error (MAPE) and Secant Cosine Calculation methods.