IN-PERSON London. Section A
Abstract
This paper presents a novel methodological framework utilizing Visual Artificial Intelligence (AI) techniques to investigate the relationship between urban design and walkability experiences among older adults, with the goal of deriving design guidelines to enhance their well-being. The study leverages machine learning methods such as Object Detection and Image Segmentation to quantify urban design elements using street-view images. Data from the Hong Kong Travel Characteristics Survey are employed to calculate older adults’ walking choice as a walkability index. Statistical analyses, including Linear Regression and Geographically Weighted Regression, are utilized to explore correlations between urban elements and walkability, considering both quantitative and spatial dimensions. The findings demonstrate significant correlations between specific urban elements like benches, trees, crosswalks, and streetlights with older adults’ walkability. Combinations of urban elements, such as benches and sidewalks, are identified as contributing significantly to enhanced walkability. Qualitative analyses using street view images further inform the development of design guidelines aimed at creating urban environments conducive to physical activity, social interaction, and overall well-being among older adults. The implications of this research extend to the development of human-centric urban design principles and the potential use of machine learning models to predict walkability based on street view images. By considering the human perspective by employing Visual AI technologies, this study provides valuable insights for urban designers and policymakers to create more inclusive and walkable urban environments, particularly benefiting older adult populations.
Haozhuo Yang is a candidate for the Master of Architecture in Urban Design at Harvard Graduate School of Design. He holds a Bachelor of Architecture from Tongji University. His research is centered on the convergence of computational methods and urbanism, exploring the integration of data-driven approaches to urban design.
Hanna Negami is a Data Strategist with Perkins Eastman’s Design Strategy team. She completed her Ph.D. in cognitive neuroscience at the University of Waterloo, where she investigated emotional response to built space. At Perkins Eastman, she leverages her expertise in the psychology of architecture to support human-centered design-strategy decisions.
Emily Chmielewski believes research has an important role in the design process and that creating a culture of inquiry is essential to practicing good design. She is the Director of the Design Research Department at the global design firm Perkins Eastman. Emily holds degrees in architecture and environment-behavior research and has over twenty years of experience in the AEC industry. Her work explores how the built environment affects people’s perceptions, behaviors, and well-being. Emily is also a passionate advocate for research in practice, sharing her expertise industry-wide through mentorship, professional discourse, and by fostering peer networks.
A native of Colombia, Alejandro Giraldo has practiced architecture for over 25 years in South America and the United States. Being a connector – of people, ideas, projects, and communities—is his natural drive. Alejandro believes in the power of collaboration and feels that the most successful projects involve strong partnerships with clients and consultants. His design work and market expertise have been recognized with various architectural awards and featured widely in publications. Alejandro has served as panelist and presenter at local, state, and national conferences. He has architectural-design teaching experience and is an active proponent of intentional mentorship programs, both within the firm and industry-wide
11:00 am - 12:30 pm
Thursday 27th June, 2024