{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T01:54:54Z","timestamp":1783389294827,"version":"3.54.6"},"reference-count":57,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T00:00:00Z","timestamp":1757894400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"General Project of Social Science Foundation of Hubei Province","award":["HBSKJJ20233416"],"award-info":[{"award-number":["HBSKJJ20233416"]}]},{"name":"General Project of Social Science Foundation of Hubei Province","award":["JCX2023022"],"award-info":[{"award-number":["JCX2023022"]}]},{"name":"Key Project for Graduate Students\u2019 Innovation and Entrepreneurship of Wuhan University of Science and Technology","award":["HBSKJJ20233416"],"award-info":[{"award-number":["HBSKJJ20233416"]}]},{"name":"Key Project for Graduate Students\u2019 Innovation and Entrepreneurship of Wuhan University of Science and Technology","award":["JCX2023022"],"award-info":[{"award-number":["JCX2023022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>With rapid urbanization and increasing emphasis on sustainable mobility, slow-moving traffic systems, including pedestrian and cycling infrastructure, have become critical to urban transportation and quality of life. Conventional assessment methods are labor-intensive, time-consuming, and limited in coverage. Leveraging advances in deep learning and computer vision, this study develops a framework for bottleneck detection using street-level imagery and the You Only Look Once version 5 (YOLOv5) model. An evaluation system comprising 15 indicators across continuity, safety, and comfort is established. In a case study of Wuhan\u2019s Third Ring Road, the YOLOv5 model achieved 98.9% mean Average Precision (mAP)@0.5, while spatial hotspot analysis (p &lt; 0.05) identified severe demand\u2013infrastructure mismatches in southeastern Wuhan, contrasted with fewer problems in the northern region due to stronger management. To ensure adaptability, a dynamic optimization mechanism integrating temporal imagery updates, transfer learning, and collaborative training is proposed. The findings demonstrate the effectiveness of street-level remote sensing for large-scale urban diagnostics, extend the application of deep learning in mobility research, and provide practical insights for data-driven planning and governance of slow-moving traffic systems in high-density cities.<\/jats:p>","DOI":"10.3390\/ijgi14090351","type":"journal-article","created":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T16:27:33Z","timestamp":1757953653000},"page":"351","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Automated Identification and Spatial Pattern Analysis of Urban Slow-Moving Traffic Bottlenecks Using Street View Imagery and Deep Learning"],"prefix":"10.3390","volume":"14","author":[{"given":"Zixuan","family":"Guo","sequence":"first","affiliation":[{"name":"School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China"},{"name":"Hubei Provincial Engineering Research Center of Urban Regeneration, Wuhan University of Science and Technology, Wuhan 430065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiushuang","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.trf.2025.02.005","article-title":"How does the built environment affect pedestrian perception of road safety on sidewalks? Evidence from eye-tracking experiments","volume":"110","author":"Yao","year":"2025","journal-title":"Transp. Res. Part F"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1177\/0361198118792767","article-title":"A Framework for Identifying Recurring Bottlenecks in the State Planning Process in Colorado","volume":"2672","author":"Deselnicu","year":"2018","journal-title":"Transp. Res. Rec."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"107805","DOI":"10.1016\/j.engappai.2023.107805","article-title":"An integrated deep learning approach for assessing the visual qualities of built environments utilizing street view images","volume":"130","author":"Zhao","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kang, Y., Kim, J., Park, J., and Lee, J. (2023). Assessment of Perceived and Physical Walkability Using Street View Images and Deep Learning Technology. Isprs Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12050186"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"105073","DOI":"10.1016\/j.landurbplan.2024.105073","article-title":"Evaluating the subjective perceptions of streetscapes using street-view images","volume":"247","author":"Ogawa","year":"2024","journal-title":"Landsc. Urban Plan."},{"key":"ref_6","first-page":"20240095","article-title":"Addressing the urban congestion challenge based on traffic bottlenecks","volume":"382","author":"Lieberthal","year":"2024","journal-title":"Philos. Trans. A Math. Phys. Eng. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1137\/18M1172211","article-title":"Well-Posedness for Scalar Conservation Laws with Moving Flux Constraints","volume":"79","author":"Liard","year":"2019","journal-title":"Siam J. Appl. Math."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.2105\/AJPH.93.9.1509","article-title":"Promoting safe walking and cycling to improve public health: Lessons from the Netherlands and Germany","volume":"93","author":"Pucher","year":"2003","journal-title":"Am. J. Public Health"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2050008","DOI":"10.1142\/S2345748120500086","article-title":"China\u2019s Strategies and Policies for Regional Development During the Period of the 14th Five-Year Plan","volume":"8","author":"Wei","year":"2020","journal-title":"Chin. J. Urban Environ. Stud."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"112991","DOI":"10.1016\/j.eswa.2019.112991","article-title":"A novel vehicle lateral positioning methodology based on the integrated deep neural network","volume":"142","author":"Zheng","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"741","DOI":"10.3390\/ijgi4020741","article-title":"Real-Time Sidewalk Slope Calculation through Integration of GPS Trajectory and Image Data to Assist People with Disabilities in Navigation","volume":"4","author":"Yihan","year":"2015","journal-title":"ISPRS Int. J. Geo-Inf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e2220417120","DOI":"10.1073\/pnas.2220417120","article-title":"Urban visual intelligence: Uncovering hidden city profiles with street view images","volume":"120","author":"Fan","year":"2023","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"129415","DOI":"10.1016\/j.physa.2023.129415","article-title":"Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model","volume":"633","author":"Hou","year":"2024","journal-title":"Phys. A-Stat. Mech. Its Appl."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Petrasova, A., Hipp, J.A., and Mitasova, H. (2019). Visualization of Pedestrian Density Dynamics Using Data Extracted from Public Webcams. Isprs Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8120559"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bolten, N., and Caspi, A. (2021). Towards routine, city-scale accessibility metrics: Graph theoretic interpretations of pedestrian access using personalized pedestrian network analysis. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0248399"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1080\/13682199.2015.1109783","article-title":"Performance evaluation for feature extractors on street view images","volume":"64","author":"Guzel","year":"2016","journal-title":"Imaging Sci. J."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wang, J., Kong, Y., Fu, T., and Stipancic, J. (2017). The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0184564"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5861414","DOI":"10.1155\/2019\/5861414","article-title":"Identifying Recurring Bottlenecks on Urban Expressway Using a Fusion Method Based on Loop Detector Data","volume":"2019","author":"Tang","year":"2019","journal-title":"Math. Probl. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"4827","DOI":"10.1109\/TVT.2020.2973404","article-title":"Congestion Propagation Based Bottleneck Identification in Urban Road Networks","volume":"69","author":"Li","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6888115","DOI":"10.1155\/2022\/6888115","article-title":"Freeway Traffic Speed Prediction under the Intelligent Driving Environment: A Deep Learning Approach","volume":"2022","author":"Hua","year":"2022","journal-title":"J. Adv. Transp."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"103367","DOI":"10.1016\/j.trc.2021.103067","article-title":"Deep visual Re-identification with confidence","volume":"126","author":"Adaimi","year":"2021","journal-title":"Transp. Res. Part C-Emerg. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"103931","DOI":"10.1016\/j.aei.2024.102931","article-title":"Automatic identification of bottlenecks for ambulance passage on urban streets: A deep learning-based approach","volume":"62","author":"Pan","year":"2024","journal-title":"Adv. Eng. Inform."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.ypmed.2007.08.004","article-title":"Accessibility and connectivity in physical activity studies: The impact of missing pedestrian data","volume":"46","author":"Chin","year":"2008","journal-title":"Prev. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1186\/1476-072X-12-58","article-title":"Using simple agent-based modeling to inform and enhance neighborhood walkability","volume":"12","author":"Badland","year":"2013","journal-title":"Int. J. Health Geogr."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1049\/iet-its.2017.0284","article-title":"Data-driven approach for identifying spatiotemporally recurrent bottlenecks","volume":"12","author":"Song","year":"2018","journal-title":"Iet Intell. Transp. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"030006","DOI":"10.1063\/5.0004878","article-title":"Analysis Of The Pedestrian Path Toward Duren Kalibata Train Station As A Part Of The Transit Development Area","volume":"Volume 2227","author":"Pandapotan","year":"2020","journal-title":"AIP Conference Proceedings"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"70937","DOI":"10.1007\/s11042-024-18161-8","article-title":"Efficient traffic monitoring and congestion control with GGA and deep CNN-LSTM using VANET","volume":"83","author":"Budholiya","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1080\/10095020.2021.1978276","article-title":"Understanding the pattern and mechanism of spatial concentration of urban land use, population and economic activities: A case study in Wuhan, China","volume":"24","author":"Li","year":"2021","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gallego-Valades, A., Rodenas-Rigla, F., and Garces-Ferrer, J. (2021). Spatial Distribution of Public Housing and Urban Socio-Spatial Inequalities: An Exploratory Analysis of the Valencia Case. Sustainability, 13.","DOI":"10.3390\/su132011381"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"102872","DOI":"10.1016\/j.inffus.2024.102872","article-title":"ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial-temporal traffic forecasting","volume":"117","author":"Shao","year":"2025","journal-title":"Inf. Fusion"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.compenvurbsys.2017.04.001","article-title":"Street level urban design qualities for walkability: Combining 2D and 3D GIS measures","volume":"64","author":"Yin","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_32","first-page":"1655","article-title":"The perceived importance and objective measurement of walkability in the built environment rating","volume":"47","author":"Zhang","year":"2020","journal-title":"Environ. Plan. B-Urban Anal. City Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"11465","DOI":"10.1109\/JIOT.2023.3244182","article-title":"Adaptive Graph Fusion Convolutional Recurrent Network for Traffic Forecasting","volume":"10","author":"Xu","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/mice.13334","article-title":"A convergent cross-mapping approach for unveiling congestion spatial causality in urban traffic networks","volume":"40","author":"Mao","year":"2025","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"76684","DOI":"10.1109\/ACCESS.2025.3565300","article-title":"A Review on Research and Application of AI-Based Image Analysis in the Field of Computer Vision","volume":"13","author":"Wu","year":"2025","journal-title":"IEEE Access"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1016\/j.tra.2005.02.022","article-title":"Congestion and safety: A spatial analysis of London","volume":"39","author":"Noland","year":"2005","journal-title":"Transp. Res. Part A-Policy Pract."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.compenvurbsys.2010.12.004","article-title":"Analysis of traffic hazard intensity: A spatial epidemiology case study of urban pedestrians","volume":"35","author":"Ha","year":"2011","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1080\/17457300.2012.724690","article-title":"Spatial environmental risk factors for pedestrian injury collisions in Ciudad Juarez, Mexico (20082009): Implications for urban planning","volume":"20","author":"Hernandez","year":"2013","journal-title":"Int. J. Inj. Control Saf. Promot."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.compenvurbsys.2016.03.007","article-title":"Visibility of urban activities and pedestrian routes: An experiment in a virtual environment","volume":"58","author":"Natapov","year":"2016","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Droj, G., Droj, L., and Badea, A.-C. (2022). GIS-Based Survey over the Public Transport Strategy: An Instrument for Economic and Sustainable Urban Traffic Planning. ISPRS Int. J. Geo-Inf., 11.","DOI":"10.3390\/ijgi11010016"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Kormecli, P.S. (2023). Analysis of Walkable Street Networks by Using the Space Syntax and GIS Techniques: A Case Study of cankiri City. ISPRS Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12060216"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Jerath, K., Gayah, V.V., and Brennan, S.N. (2024). Mitigating delay due to capacity drop near freeway bottlenecks: Zones of influence of connected vehicles. PLoS ONE, 19.","DOI":"10.1371\/journal.pone.0301188"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1007\/s43762-021-00024-9","article-title":"Street life and pedestrian activities in smart cities: Opportunities and challenges for computational urban science","volume":"1","author":"Fan","year":"2021","journal-title":"Comput. Urban Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Huang, X., Zeng, L., Liang, H., Li, D., Yang, X., and Zhang, B. (2024). Comprehensive walkability assessment of urban pedestrian environments using big data and deep learning techniques. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-78041-x"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.trd.2005.05.002","article-title":"Correlation or causality between the built environment and travel behavior? Evidence from Northern California","volume":"10","author":"Handy","year":"2005","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.jtrangeo.2019.03.010","article-title":"Active travel for active ageing in China: The role of built environment","volume":"76","author":"Cheng","year":"2019","journal-title":"J. Transp. Geogr."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Oluyomi, A.O., Knell, G., Durand, C.P., Mercader, C., Salvo, D., Sener, I.N., Gabriel, K.P., Hoelscher, D.M., and Kohl, H.W. (2019). Foot-based audit of streets adjacent to new light rail stations in Houston, Texas: Measurement of health-related characteristics of the built environment for physical activity research. BMC Public Health, 19.","DOI":"10.1186\/s12889-019-6560-4"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.jth.2017.01.010","article-title":"Objective assessment of station approach routes.: Development and reliability of an audit for walking environments around metro stations in China","volume":"4","author":"Sun","year":"2017","journal-title":"J. Transp. Health"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.envint.2016.05.032","article-title":"Car free cities: Pathway to healthy urban living","volume":"94","author":"Nieuwenhuijsen","year":"2016","journal-title":"Environ. Int."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.cities.2019.01.003","article-title":"Associations between overhead-view and eye-level urban greenness and cycling behaviors","volume":"88","author":"Lu","year":"2019","journal-title":"Cities"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s12942-019-0182-z","article-title":"The linkage between the perception of neighbourhood and physical activity in Guangzhou, China: Using street view imagery with deep learning techniques","volume":"18","author":"Wang","year":"2019","journal-title":"Int. J. Health Geogr."},{"key":"ref_52","first-page":"1231","article-title":"Exploring the coherence and divergence between the objective and subjective measurement of streetscape perceptions at the neighborhood level: A case study in Shanghai","volume":"52","author":"Song","year":"2025","journal-title":"Environ. Plan. B-Urban Anal. City Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1111\/j.1467-8306.2004.09402005.x","article-title":"Tobler\u2019s First Law and Spatial Analysis","volume":"94","author":"Miller","year":"2004","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","article-title":"LOCAL INDICATORS OF SPATIAL ASSOCIATION\u2014LISA","volume":"27","author":"Anselin","year":"1995","journal-title":"Geogr. Anal."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/0166-0462(95)02111-6","article-title":"Simple diagnostic tests for spatial dependence","volume":"26","author":"Anselin","year":"1996","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1111\/j.1538-4632.1991.tb00228.x","article-title":"Properties of Tests for Spatial Dependence in Linear-Regression Models","volume":"23","author":"Anselin","year":"1991","journal-title":"Geogr. Anal."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"103694","DOI":"10.1016\/j.apgeog.2025.103694","article-title":"Revealing the spatiotemporal pattern of urban vibrancy at the urban agglomeration scale: Evidence from the Pearl River Delta, China","volume":"181","author":"Jiang","year":"2025","journal-title":"Appl. Geogr."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/9\/351\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:45:51Z","timestamp":1760035551000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/14\/9\/351"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,15]]},"references-count":57,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["ijgi14090351"],"URL":"https:\/\/doi.org\/10.3390\/ijgi14090351","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,15]]}}}