Navigation behaviour of visitors in museums based on visibility analysis and neural network simulation

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.

KEYWORDS:

• Visibility graph analysis
• space syntax
• exploratory navigation
• movement behaviour
• neural network
• Islamic Revolution and Iran-Iraq war museum

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Fateme Rashidi Jouibari is an Architecture student at Iran University of Science & Technology. She graduated with an MS in Architecture in 2019. Her research concentrates on Visitor Studies, Environmental Psychology, Spatial Cognition, Behavioral Sciences and Environment & Planning.

Mohsen Faizi is a Professor of Landscape Architecture in the school of Architecture and Environmental Design, at Iran University of Science & Technology. Faizi completed his graduate and post graduate studies at IUST and gained his Ph.D. from the University of Sheffield. In the “12th Distinguished Researchers and Technologists Award, Faizi was selected as the country's eminent researcher in the Art Group by the Ministry of Science, Research and Technology. At present he is a member of IUST's Board of Promotions. He is the Chief Editor in the International Journal of Architectural Engineering & Urban Planning of IUST. Also he is a visit lecturer in the Department of Landscape Architecture at Sheffield University, UK. His research interest contains Landscape Architecture, Sustainable Architecture and Environmental Design.

Mehdi Khakzand is an Associate Professor of Landscape Architecture at Iran University of Science & Technology. He gained his Ph.D. in Landscape Architecture at IUST in 2009. He is the Faculty member in the school of Architecture and Environmental Design, at Iran University of Science & Technology. His research interests contains Architecture, Sustainable Architecture, Environmental Design, Landscape Architecture and Environmental Psychology.

Mohammad javad Shekari is a student of Electrical engineering at Iran University of Science & Technology. He graduated with an MS in 2019. His research field contains Intelligent Control, Fuzzy Systems, Nonlinear Control and Neural Network (NN).