Abstract
ABSTRACT Analysing the navigation behaviour in a built environment without a particular destination is a complicated issue when simulating pedestrian behaviour. This navigation is called exploratory navigation. This paper aims to investigate the spatial characteristics of a built environment which affect exploratory navigation. It focuses on visibility graph analysis (VGA) and uses the artificial neural network (ANN) for predicting navigation behaviours of visitors in museums. The movement data of visitors in the Islamic Revolution and Iran-Iraq War Museum (IRIIWM) in Tehran, Iran are collected from an observational study. The neural network analyzes the movement features of visitors and produces one single route containing all important movement characteristics of actual visitors. The results show that the network chooses its next target based on spatial visibility, visual perception, distance to a particular section, direction change, visual connectivity, and visual integration. The turn patterns and visual attractors also affect exploratory navigation.
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