{"id":"https://openalex.org/W2968014400","doi":"https://doi.org/10.1109/tits.2019.2931892","title":"An Intelligence-Based Approach for Prediction of Microscopic Pedestrian Walking Behavior","display_name":"An Intelligence-Based Approach for Prediction of Microscopic Pedestrian Walking Behavior","publication_year":2019,"publication_date":"2019-08-08","ids":{"openalex":"https://openalex.org/W2968014400","doi":"https://doi.org/10.1109/tits.2019.2931892","mag":"2968014400"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2931892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2931892","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101777957","display_name":"Yi Ma","orcid":"https://orcid.org/0000-0001-6568-2581"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Ma","raw_affiliation_strings":["Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090768303","display_name":"Eric Wai Ming Lee","orcid":"https://orcid.org/0000-0002-3156-2036"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Eric Waiming Lee","raw_affiliation_strings":["Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109635532","display_name":"Zuoan Hu","orcid":"https://orcid.org/0000-0002-5723-1665"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuoan Hu","raw_affiliation_strings":["Department of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Department of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083891511","display_name":"Meng Shi","orcid":"https://orcid.org/0000-0001-9765-3101"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Meng Shi","raw_affiliation_strings":["Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023722015","display_name":"Richard K.K. Yuen","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Richard Kowkkit Yuen","raw_affiliation_strings":["Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101777957"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":2.7814,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.89496771,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"20","issue":"10","first_page":"3964","last_page":"3980"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.9018601179122925},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6396263837814331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6123347878456116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5583020448684692},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5489089488983154},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.47296756505966187},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46296998858451843},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.45713648200035095},{"id":"https://openalex.org/keywords/preferred-walking-speed","display_name":"Preferred walking speed","score":0.41181039810180664},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.39909282326698303},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23418661952018738},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15160304307937622},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14094442129135132},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.12356945872306824},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.09419125318527222},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07877737283706665}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.9018601179122925},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6396263837814331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6123347878456116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5583020448684692},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5489089488983154},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.47296756505966187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46296998858451843},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.45713648200035095},{"id":"https://openalex.org/C70770792","wikidata":"https://www.wikidata.org/wiki/Q7239848","display_name":"Preferred walking speed","level":2,"score":0.41181039810180664},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.39909282326698303},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23418661952018738},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15160304307937622},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14094442129135132},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.12356945872306824},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.09419125318527222},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07877737283706665},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2931892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2931892","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G454892167","display_name":null,"funder_award_id":"11204117","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"}],"funders":[{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1567928412","https://openalex.org/W1573503290","https://openalex.org/W1586335931","https://openalex.org/W1848277695","https://openalex.org/W1888172398","https://openalex.org/W1969262165","https://openalex.org/W1976929923","https://openalex.org/W1982675814","https://openalex.org/W1995225412","https://openalex.org/W2000712959","https://openalex.org/W2004641798","https://openalex.org/W2011042166","https://openalex.org/W2011913982","https://openalex.org/W2013392773","https://openalex.org/W2018875010","https://openalex.org/W2018937623","https://openalex.org/W2029959244","https://openalex.org/W2036536917","https://openalex.org/W2040707847","https://openalex.org/W2042917546","https://openalex.org/W2059303086","https://openalex.org/W2061791090","https://openalex.org/W2061802164","https://openalex.org/W2065042410","https://openalex.org/W2071292957","https://openalex.org/W2073682681","https://openalex.org/W2078255640","https://openalex.org/W2079291076","https://openalex.org/W2080828328","https://openalex.org/W2082292845","https://openalex.org/W2082301371","https://openalex.org/W2091795836","https://openalex.org/W2106833987","https://openalex.org/W2110707640","https://openalex.org/W2112164016","https://openalex.org/W2128731188","https://openalex.org/W2129589491","https://openalex.org/W2129710987","https://openalex.org/W2132505539","https://openalex.org/W2135674171","https://openalex.org/W2137983211","https://openalex.org/W2139050361","https://openalex.org/W2148961728","https://openalex.org/W2153635508","https://openalex.org/W2172055967","https://openalex.org/W2242940318","https://openalex.org/W2277256083","https://openalex.org/W2286744228","https://openalex.org/W2290654117","https://openalex.org/W2337895322","https://openalex.org/W2395550967","https://openalex.org/W2424778531","https://openalex.org/W2475723319","https://openalex.org/W2518708963","https://openalex.org/W2546124871","https://openalex.org/W2607296803","https://openalex.org/W2608611683","https://openalex.org/W2799059904","https://openalex.org/W2801667201","https://openalex.org/W2911273949","https://openalex.org/W2963001155","https://openalex.org/W2964230007","https://openalex.org/W3101207396","https://openalex.org/W3121926921","https://openalex.org/W3146803896","https://openalex.org/W4241069851","https://openalex.org/W4252143037","https://openalex.org/W4297802673","https://openalex.org/W6633655026","https://openalex.org/W6634288218","https://openalex.org/W6638898290","https://openalex.org/W6694552041"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W4205958986","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W2471005005","https://openalex.org/W591021443"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,49,70,207],"locally":[4],"microscopic":[5,99,146,220],"pedestrian":[6,22,79,89,100,135,147,221,243],"walking":[7,23,59,80,90,101,136,148,222],"behavior":[8,24,81,91,149],"and":[9,35,53,55,92,159,191],"proposes":[10],"an":[11,203],"intelligent":[12],"behavioral":[13,60],"learning":[14,113],"approach":[15,139,214,232],"for":[16,235],"its":[17],"prediction.":[18],"In":[19],"this":[20],"approach,":[21],"was":[25,67,108,117,140],"modeled":[26],"as":[27,119,188],"a":[28,42,71,242],"special":[29],"artificial":[30],"neural":[31,65,125],"network":[32,66,126],"whose":[33],"input":[34],"output":[36],"layers":[37],"were":[38,163,200],"used":[39],"to":[40,85,93,97,110,165,215],"accommodate":[41],"pedestrian's":[43],"perceived":[44],"environmental":[45],"information":[46,48],"(e.g.,":[47],"the":[50,95,112,115,124,130,143,160,167,170,172,175,197,212,230,238],"destination,":[51],"obstacles,":[52],"neighbors)":[54],"his":[56],"or":[57],"her":[58],"response,":[61],"respectively.":[62],"The":[63,138,155],"developed":[64,213],"trained":[68],"based":[69],"large":[72],"volume":[73],"of":[74,77,88,145,169,174,218,237,241],"data":[75],"samples":[76],"real-life":[78,153],"(3813":[82],"training":[83],"samples)":[84],"acquire":[86],"knowledge":[87],"develop":[94],"ability":[96],"predict":[98],"behavior.":[102,137,223],"A":[103],"quantitative":[104],"evaluation":[105],"index,":[106],"R-squared,":[107],"calculated":[109,118,164,187],"evaluate":[111,166],"performance;":[114],"mean":[116,173],"0.900,":[120],"which":[121,194],"indicates":[122,195],"that":[123,196,229],"can":[127],"well":[128],"capture":[129],"underlying":[131],"decision-making":[132],"mechanism":[133],"behind":[134],"verified":[141],"by":[142],"prediction":[144,198],"details":[150],"in":[151,182],"two":[152,183],"scenarios.":[154],"vector":[156,176],"displacement":[157,177],"error":[158,162,178],"speed":[161,180],"quality":[168],"prediction;":[171],"(the":[179],"error)":[181],"scenarios":[184],"were,":[185],"respectively,":[186],"0.192":[189],"(0.116)":[190],"0.226":[192],"(0.096),":[193],"results":[199],"acceptable":[201],"from":[202],"engineering":[204],"perspective.":[205],"Based":[206],"these":[208],"results,":[209],"we":[210],"consider":[211],"be":[216],"capable":[217],"predicting":[219],"Moreover,":[224],"extended":[225],"application":[226],"also":[227],"shows":[228],"proposed":[231],"has":[233],"promise":[234],"simulation":[236],"short-term":[239],"flow":[240],"crowd.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
