Mapping User Experiences around Transit Stops Using Computer Vision Technology: Action Priorities from Cairo

Shereen Wael (), Abeer Elshater and Samy Afifi
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Shereen Wael: Department of Urban Design and Planning, Faculty of Engineering, Ain Shams University, Cairo 11517, ‎Egypt
Abeer Elshater: Department of Urban Design and Planning, Faculty of Engineering, Ain Shams University, Cairo 11517, ‎Egypt
Samy Afifi: Department of Urban Design and Planning, Faculty of Engineering, Ain Shams University, Cairo 11517, ‎Egypt

Sustainability, 2022, vol. 14, issue 17, 1-20

Abstract: In the field of urban studies, artificial intelligence technology offers potential applications. There are, however, limited sources on how technology can contribute to the study of user experiences in city contexts. This study examined the factors affecting user experiences around three exits of one of the Cairo Metro stops in Ramses Square in Cairo, Egypt. Using a Geographical Information System (GIS) and GoodVision Video Insights and spatial analysis was conducted for the selected built environment. Our results demonstrate that pedestrian flow, thermal comfort, safety levels, and destination proximity contribute to the user experience. Our results also prove that urban configuration with multiple elements in the stations’ context strongly affects metro user experience. As such, three levels of priorities were suggested to guide city planners, urban designers, and landscape architects through developing or designing stations with user experience in mind. For future studies, this study offers a valuable method for developing qualitative and quantitative analyses of pedestrian movement in stations’ contexts.

Keywords: artificial intelligence; computer vision; level of service; transit-oriented development; urban configuration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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