Exploring the Relationship between Human Walking Trajectories and Physical-Visual Environmental: An Application of Artificial Intelligence and Spatial Analysis
Active transportation, especially walking, plays a vital role in ensuring a healthy and livable community. Walking, as a type of physical activity, helps in reducing the risk of health-related issues. Since the surrounding built environment around the walking site impacts walking experience, there is a need to investigate the influence of the physical and visual environmental attributes on pedestrian walking activity. In this study, the authors investigated the connection between human walking activities and surrounding physical and visual environment at a street level by applying artificial intelligence and spatial statistical analysis. A survey was initiated to collect a large amount of human trajectory data from Kalamazoo, Michigan through a mobile application developed by the authors' research team. Google Street View (GSV) images were obtained to objectively assess the relationship between human trajectory data and visual environmental attributes. Statistical analysis results showed human walking activities were positively correlated with surrounding visual environmental attributes such as building enclosure, street light/pole, traffic sign and billboard, street greenery, and the enclosure of the sky view factor. In addition, the authors computed the visual environmental score (VES) along the sidewalks to assess the effect of visual environmental attributes on pedestrian walking experiences. The result showed that the VES index along the sidewalk segments varied by the purpose of pedestrian trip, but the VES index was positively correlated with the number of pedestrian trips.
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Supplemental Notes:
- This paper was sponsored by TRB committee ACH10 Standing Committee on Pedestrians.
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Corporate Authors:
Transportation Research Board
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Authors:
- Hasan, Md Mehedi
- Oh, Jun-Seok
- Kwigizile, Valerian
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Conference:
- Transportation Research Board 100th Annual Meeting
- Location: Washington DC, United States
- Date: 2021-1-5 to 2021-1-29
- Date: 2021
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: 21p
Subject/Index Terms
- TRT Terms: Artificial intelligence; Built environment; Data collection; Mobile applications; Pedestrian movement; Spatial analysis; Trajectory; Walking
- Identifier Terms: Google Street View
- Geographic Terms: Kalamazoo (Michigan)
- Subject Areas: Data and Information Technology; Operations and Traffic Management; Pedestrians and Bicyclists;
Filing Info
- Accession Number: 01764135
- Record Type: Publication
- Report/Paper Numbers: TRBAM-21-02542
- Files: TRIS, TRB, ATRI
- Created Date: Feb 4 2021 11:00AM