On the use of a simulation framework for studying accessibility challenges faced by people with disabilities in indoor environments

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Authors
Garfias, Francisco R.
Namboodiri, Vinod
Advisors
Issue Date
2024
Type
Conference paper
Keywords
3D modeling , Accessibility , Algorithms , Indoor navigation , Simulation
Research Projects
Organizational Units
Journal Issue
Citation
Garfias, F.J.R., Namboodiri, V. On the use of a simulation framework for studying accessibility challenges faced by people with disabilities in indoor environments. (2024). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14750 LNCS, pp. 31-37. DOI: 10.1007/978-3-031-62846-7_4
Abstract

Navigating indoor spaces is known to be significantly challenges for individuals with mobility and sensory impairments due to the presence of physical barriers and inadequate accessible signage. Current laws and efforts have not led to meeting diverse needs of these populations. In this work we provide a brief introduction to MABLESim (Mapping for Accessible BuiLt Environments Simulator), a simulation framework for studying indoor space accessibility. MABLESim recreates digital models of indoor environments, allowing for the simulation of diverse mobility scenarios for individuals with varying abilities. MABLESim enables the analysis of critical factors important for efficient mobility in indoor spaces such as route complexity and disability characteristics. Through careful configuration of simulation parameters, MABLESim facilitates the assessment of accessibility challenges in both simple and complex indoor spaces. This framework offers a tool for designers and planners to visualize and address accessibility barriers in built environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Table of Contents
Description
19th International Conference on Computers Helping People with Special Needs, ICCHP 2024
8 July 2024 through 12 July 2024
Publisher
Springer Science and Business Media Deutschland GmbH
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Book Title
Series
PubMed ID
ISSN
0302-9743
EISSN