Navigation behaviour of visitors in museums based on visibility analysis and neural network simulation
Bibliographic Data
| ID | 7928470 |
|---|---|
| Authors | Fateme Rashidi Jouibari (School of Architecture and Environmental Design, Iran University of Science & Technology, Tehran, Iran), Mohsen Faizi (0000-0003-1022-0990, School of Architecture and Environmental Design, Iran University of Science & Technology, Tehran, Iran), Mehdi Khakzand (0000-0001-9390-3433, School of Architecture and Environmental Design, Iran University of Science & Technology, Tehran, Iran, corresponding author), Mohammad javad Shekari (School of electrical engineering, Iran University of Science & Technology, Tehran, Iran), M Shekari (Iran University of Science and Technology) |
| Year | 2021 |
| Volume | 36 |
| Issue | 1 |
| Pages | 30-47 |
| Publication date | 2021-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Museum Management and Curatorship (JOURNAL) |
| Journal identifiers | ISSN: 0964-7775 • E-ISSN: 1872-9185 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09647775.2020.1773302 |
| OpenAlex | W3036238216 |
| Language | EN |
| Citations received | 3 |
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
Artificial neural network · Computer vision · Geography · Pedestrian · Perception · Visibility · Computer Science · Psychology · Spatial Cognition and Navigation · Urban Design and Spatial Analysis · Urban Green Space and Health · Artificial Intelligence
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |