A probabilistic AI-based pedestrian volume estimation model for street-level urban management
Bibliographic Data
| ID | 12295290 |
|---|---|
| Authors | Chul Woong Park (0000-0002-5764-2464, Korea Advanced Institute of Science and Technology), Wonjun No (0000-0001-6069-7274, Korea Research Institute for Human Settlements), Young‐chul Kim (0000-0001-7945-028X, Korea Advanced Institute of Science and Technology, corresponding author) |
| Year | 2025 |
| Volume | 129 |
| Pages | 104437-104437 |
| Publication date | 2025-10-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Transport Geography (JOURNAL) |
| Journal identifiers | ISSN: 0966-6923 • E-ISSN: 1873-1236 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jtrangeo.2025.104437 |
| OpenAlex | W4415199432 |
| Language | EN |
| References cited | 46 |
Artificial neural network · Bayesian network · Bayesian probability · Estimation · Pedestrian · Probabilistic logic · Statistical model · Urban area · Volume (thermodynamics · Human Mobility and Location-Based Analysis · Urban Transport and Accessibility · Video Surveillance and Tracking Methods
Trustworthy Artificial Intelligence
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From Axial to Road-Centre Lines
Origin–destination trips by purpose and time of day inferred from mobile phone data
Measuring the complexity of urban form and design
Configurational Modelling of Urban Movement Networks
Travel demand and the 3Ds
Place identity
Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network
Estimating pedestrian volume using Street View images
Advances in estimating pedestrian measures through artificial intelligence
When spatial interpolation matters
Estimating Pedestrian Flows on Street Networks
Smart curbs
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Explainable heat-related mortality with random forest and SHapley Additive exPlanations (SHAP) models
Exploring the association between street built environment and street vitality using deep learning methods
How urban land use influences commuting flows in Wuhan, Central China
Pedestrian volume prediction with high spatiotemporal granularity in urban areas by the enhanced learning model
Understanding aggregate human mobility patterns using passive mobile phone location data
Bayesian spatio-temporal models for mapping urban pedestrian traffic
The Usability of Unmanned Aerial Vehicles (UAVs) for Pedestrian Observation
Effects of street-level physical environment and zoning on walking activity in Seoul, Korea
Examining the association between the built environment and pedestrian volume using street view images
Pedestrian-oriented development in Beirut
Development of an AI advisor for conceptual land use planning
The impact of street network connectivity on pedestrian volume
| Citation velocity | historical |
|---|---|
| Highly cited | No |