{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T18:52:32Z","timestamp":1770490352956,"version":"3.49.0"},"reference-count":50,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,8]],"date-time":"2020-03-08T00:00:00Z","timestamp":1583625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41271399"],"award-info":[{"award-number":["41271399"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFB0501403"],"award-info":[{"award-number":["2016YFB0501403"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Special Fund for Surveying, Mapping and Geoinformation Research in the Public Interest","award":["201512015"],"award-info":[{"award-number":["201512015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Alleviating public traffic congestion is an efficient and effective way to improve the travel time reliability and quality of public transport services. The existing public network optimization models usually ignored the essential impact of public traffic congestion on the performance of public transport service. To address this problem, this study proposes a data-based methodology to estimate the traffic congestion of road segments between bus stops (RSBs). The proposed methodology involves two steps: (1) Extracting three traffic indicators of the RSBs from smart card data and bus trajectory data; (2) The self-organizing map (SOM) is used to cluster and effectively recognize traffic patterns embedded in the RSBs. Furthermore, a congestion index for ranking the SOM clusters is developed to determine the congested RSBs. A case study using real-world datasets from a public transport system validates the proposed methodology. Based on the congested RSBs, an exploratory example of public transport network optimization is discussed and evaluated using a genetic algorithm. The clustering results showed that the SOM could suitably reflect the traffic characteristics and estimate traffic congestion of the RSBs. The results obtained in this study are expected to demonstrate the usefulness of the proposed methodology in sustainable public transport improvements.<\/jats:p>","DOI":"10.3390\/ijgi9030152","type":"journal-article","created":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T05:37:34Z","timestamp":1583732254000},"page":"152","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Public Traffic Congestion Estimation Using an Artificial Neural Network"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8765-1639","authenticated-orcid":false,"given":"Yanyan","family":"Gu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yandong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center for Geospatial Information Technology, Wuhan 430079, China"},{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shihai","family":"Dong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.trb.2014.01.003","article-title":"Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding","volume":"61","author":"Tirachini","year":"2014","journal-title":"Transport. Res. B-Meth."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.tre.2009.11.001","article-title":"Optimizing bus stop spacing in urban areas","volume":"46","author":"Ibeas","year":"2010","journal-title":"Transport. Res. E-Log."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.trb.2015.03.002","article-title":"Planning, operation, and control of bus transport systems: A literature review","volume":"77","author":"Delgado","year":"2015","journal-title":"Transport. Res. B-Meth."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1061\/(ASCE)0733-947X(2006)132:1(40)","article-title":"Optimal Transit Route Network Design Problem with Variable Transit Demand: Genetic Algorithm Approach","volume":"132","author":"Fan","year":"2006","journal-title":"J. Transp. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/0191-2615(88)90042-2","article-title":"Transit system network design","volume":"22","author":"LeBlanc","year":"1988","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1111\/1467-8667.00309","article-title":"Genetic Algorithms for Optimal Urban Transit Network Design","volume":"18","author":"Chakroborty","year":"2003","journal-title":"Comput-Aided. Civ. Inf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1109\/TITS.2011.2144974","article-title":"Optimization of Transit Priority in the Transportation Network Using a Genetic Algorithm","volume":"12","author":"Mesbah","year":"2011","journal-title":"IEEE T. Intell. Transp."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Gao, P., Liu, Z., Tian, K., and Liu, G. (2016). Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity. ISPRS Int. J. Geo.-Inf., 5.","DOI":"10.3390\/ijgi5030034"},{"key":"ref_9","first-page":"1","article-title":"Modelling the net traffic congestion impact of bus operations in Melbourne","volume":"117","author":"Currie","year":"2018","journal-title":"Transport. Res. A-Pol."},{"key":"ref_10","first-page":"37","article-title":"The economics and engineering of bus stops: Spacing, design and congestion","volume":"59","author":"Tirachini","year":"2014","journal-title":"Transport. Res. A-Pol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"104","DOI":"10.5038\/2375-0901.20.1.6","article-title":"Impact of Different Bus Stop Designs on Bus Operating Time Components","volume":"20","author":"Liu","year":"2017","journal-title":"J. Public. Transport."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ejor.2015.05.059","article-title":"Efficiency and effectiveness in the urban public transport sector: A critical review with directions for future research","volume":"248","author":"Daraio","year":"2016","journal-title":"Eur. J. Oper. Res."},{"key":"ref_13","first-page":"501","article-title":"Vulnerability analysis for large-scale and congested road networks with demand uncertainty","volume":"46","author":"Chen","year":"2012","journal-title":"Transport. Res. A-Pol."},{"key":"ref_14","first-page":"1","article-title":"Urban Computing: Concepts, Methodologies, and Applications","volume":"5","author":"Zheng","year":"2014","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.neucom.2017.06.017","article-title":"Efficient traffic congestion estimation using multiple spatio-temporal properties","volume":"267","author":"Yang","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"128","DOI":"10.3390\/ijgi7040128","article-title":"Revealing Recurrent Urban Congestion Evolution Patterns with Taxi Trajectories","volume":"7","author":"An","year":"2018","journal-title":"ISPRS Int. J. Geo.-Inf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.trb.2013.03.008","article-title":"Travel time estimation for urban road networks using low frequency probe vehicle data","volume":"53","author":"Jenelius","year":"2013","journal-title":"Transport. Res. B-Meth."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.pmcj.2017.03.015","article-title":"Exploring traffic congestion correlation from multiple data sources","volume":"41","author":"Wang","year":"2017","journal-title":"Pervasive. Mob. Comput."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Yu, Q., Luo, Y., Chen, C., and Zheng, X. (2019). Road Congestion Detection Based on Trajectory Stay-Place Clustering. ISPRS Int. J. Geo.-Inf., 8.","DOI":"10.3390\/ijgi8060264"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.patcog.2017.03.030","article-title":"Locality constraint distance metric learning for traffic congestion detection","volume":"75","author":"Wang","year":"2018","journal-title":"Pattern Recogn."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"879","DOI":"10.5198\/jtlu.2017.980","article-title":"Transit accessibility, land development and socioeconomic priority: A typology of planned station catchment areas in the Greater Toronto and Hamilton Area","volume":"10","author":"Farber","year":"2017","journal-title":"J. Transp. Land Use"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.future.2015.11.013","article-title":"Urban traffic congestion estimation and prediction based on floating car trajectory data","volume":"61","author":"Kong","year":"2016","journal-title":"Future Gener. Comp. Sy."},{"key":"ref_23","unstructured":"Xu, L., Yue, Y., and Li, Q. (2013, January 13\u201316). Identifying Urban Traffic Congestion Pattern from Historical Floating Car Data. Proceedings of the 13th COTA International Conference of Transportation Professionals (CICTP), Shenzhen, China."},{"key":"ref_24","unstructured":"He, F., Yan, X., Liu, Y., and Ma, L. (2015, January 2\u20136). A Traffic Congestion Assessment Method for Urban Road Networks Based on Speed Performance Index. Proceedings of the 6th International Conference on Green Intelligent Transportation System and Safety (GITSS), Beijing, China."},{"key":"ref_25","unstructured":"Litman, T. (2015). Evaluating Public Transit Benefits and Costs, Victoria Transport Policy Institute."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.trb.2015.01.006","article-title":"Optimization of bus stop placement for routes on uneven topography","volume":"74","author":"Ceder","year":"2015","journal-title":"Transport. Res. B-Meth."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"24","DOI":"10.3141\/2111-04","article-title":"Assessing a Model for Optimal Bus Stop Spacing with High-Resolution Archived Stop-Level Data","volume":"2111","author":"Li","year":"2009","journal-title":"Transport. Res. Rec."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1080\/0308106042000226899","article-title":"Optimization of bus stop locations for improving transit accessibility","volume":"27","author":"Chien","year":"2004","journal-title":"Transport. Plan Techn."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.jtrangeo.2016.12.005","article-title":"Improving Bus Service Levels and social equity through bus frequency modelling","volume":"58","author":"Ruiz","year":"2017","journal-title":"J. Transp. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7200","DOI":"10.1016\/j.eswa.2014.05.034","article-title":"A simultaneous transit network design and frequency setting: Computing with bees","volume":"41","year":"2014","journal-title":"Expert. Syst. Appl."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2443","DOI":"10.1109\/TITS.2016.2644725","article-title":"A Data-Driven and Optimal Bus Scheduling Model With Time-Dependent Traffic and Demand","volume":"18","author":"Wang","year":"2017","journal-title":"Ieee. T. Intell. Transp."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.trc.2015.02.014","article-title":"A bi-level programming for bus lane network design","volume":"55","author":"Yu","year":"2015","journal-title":"Transport. Res. C-Emer."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/s12469-017-0159-x","article-title":"Transit priority lanes in the congested road networks","volume":"9","author":"Bagloee","year":"2017","journal-title":"Public Transport"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.compenvurbsys.2012.01.002","article-title":"Identifying bus stop redundancy: A gis-based spatial optimization approach","volume":"36","author":"Delmelle","year":"2012","journal-title":"Comput. Environ. Urban."},{"key":"ref_35","first-page":"28","article-title":"Bus dwell time: The effect of different fare collection systems, bus floor level and age of passengers","volume":"9","author":"Tirachini","year":"2013","journal-title":"Transp. A"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"756467438","DOI":"10.1177\/1687814016678162","article-title":"Real-time bus travel speed estimation model based on bus GPS data","volume":"8","author":"Weng","year":"2016","journal-title":"Adv. Mech. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Kohonen, T. (1995). Learning Vector Quantization. Self-Organizing Maps, Springer.","DOI":"10.1007\/978-3-642-97610-0"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.trc.2015.04.024","article-title":"A novel three-step procedure to forecast the inspection volume","volume":"56","author":"Turias","year":"2015","journal-title":"Transport. Res. C-Emer."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.landusepol.2018.12.003","article-title":"Transit oriented development among metro station areas in Shanghai, China: Variations, typology, optimization and implications for land use planning","volume":"82","author":"Li","year":"2019","journal-title":"Land Use Policy"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"11924","DOI":"10.1016\/j.eswa.2012.02.181","article-title":"A new approach for data clustering and visualization using self-organizing maps","volume":"39","author":"Shieh","year":"2012","journal-title":"Expert. Syst. Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3634","DOI":"10.1016\/j.eswa.2012.12.069","article-title":"Application of artificial neural network (ANN)\u2013self-organizing map (SOM) for the categorization of water, soil and sediment quality in petrochemical regions","volume":"40","author":"Olawoyin","year":"2013","journal-title":"Expert. Syst. Appl."},{"key":"ref_42","unstructured":"OSM (2018, September 06). Overhead Lines und Underground Cables. \u00a9 Openstreetmap Contributors, Open Database License (ODbL). Available online: https:\/\/www.openstreetmap.org\/copyright."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1007\/s11116-015-9601-6","article-title":"Activity detection and transfer identification for public transit fare card data","volume":"42","author":"Nassir","year":"2015","journal-title":"Transportation"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kohonen, T. (2001). Self-Organising Maps, Springer.","DOI":"10.1007\/978-3-642-56927-2"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"675","DOI":"10.5198\/jtlu.2017.954","article-title":"Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data","volume":"10","author":"Zhang","year":"2017","journal-title":"J. Transp. Land Use"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Wu, H., Liu, L., Yu, Y., Peng, Z., Jiao, H., and Niu, Q. (2019). An Agent-based Model Simulation of Human Mobility Based on Mobile Phone Data: How Commuting Relates to Congestion. ISPRS Int. J. Geo.-Inf., 8.","DOI":"10.20944\/preprints201906.0049.v1"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.trc.2015.12.005","article-title":"Bus priority at signalized intersections with single-lane approaches: A novel pre-signal strategy","volume":"63","author":"Guler","year":"2016","journal-title":"Transport. Res. C-Emer."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.trc.2014.05.002","article-title":"Transit network design by genetic algorithm with elitism","volume":"46","author":"Nayeem","year":"2014","journal-title":"Transport. Res. C-Emer."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5945","DOI":"10.1016\/j.eswa.2013.05.002","article-title":"Transit network design by Bee Colony Optimization","volume":"40","year":"2013","journal-title":"Expert. Syst. Appl."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"102620","DOI":"10.1016\/j.cities.2020.102620","article-title":"Social awareness of crisis events: A new perspective from social-physical network","volume":"99","author":"Dou","year":"2020","journal-title":"Cities"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/3\/152\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:05:15Z","timestamp":1760173515000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/3\/152"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,8]]},"references-count":50,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["ijgi9030152"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9030152","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,8]]}}}