{"id":"https://openalex.org/W2596110958","doi":"https://doi.org/10.1080/15472450.2017.1305271","title":"Dangerous driving behavior detection using video-extracted vehicle trajectory histograms","display_name":"Dangerous driving behavior detection using video-extracted vehicle trajectory histograms","publication_year":2017,"publication_date":"2017-03-13","ids":{"openalex":"https://openalex.org/W2596110958","doi":"https://doi.org/10.1080/15472450.2017.1305271","mag":"2596110958"},"language":"en","primary_location":{"id":"doi:10.1080/15472450.2017.1305271","is_oa":false,"landing_page_url":"https://doi.org/10.1080/15472450.2017.1305271","pdf_url":null,"source":{"id":"https://openalex.org/S172631016","display_name":"Journal of Intelligent Transportation Systems","issn_l":"1547-2442","issn":["1547-2442","1547-2450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of 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/A5100739499","display_name":"Zhijun Chen","orcid":"https://orcid.org/0000-0002-0992-2656"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhijun Chen","raw_affiliation_strings":["Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]},{"raw_affiliation_string":"National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101496742","display_name":"Chaozhong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaozhong Wu","raw_affiliation_strings":["Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103018219","display_name":"Zhen Huang","orcid":"https://orcid.org/0000-0001-9134-6629"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Huang","raw_affiliation_strings":["School of Automation, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067803203","display_name":"Nengchao Lyu","orcid":"https://orcid.org/0000-0002-0926-9140"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nengchao Lyu","raw_affiliation_strings":["Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100707167","display_name":"Zhaozheng Hu","orcid":"https://orcid.org/0000-0002-7204-2459"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaozheng Hu","raw_affiliation_strings":["Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081645776","display_name":"Ming Zhong","orcid":"https://orcid.org/0000-0002-4022-6800"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhong","raw_affiliation_strings":["Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018488940","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0002-4654-5861"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Cheng","raw_affiliation_strings":["Department of Civil and Environment Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environment Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060394098","display_name":"Bin Ran","orcid":"https://orcid.org/0000-0002-5464-0930"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Ran","raw_affiliation_strings":["Department of Civil and Environment Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environment Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100739499"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":1.7561,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.91074424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"21","issue":"5","first_page":"409","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7710158228874207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7055158019065857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6414833068847656},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.636214017868042},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4707042872905731},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.4605265259742737},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.44768714904785156},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.44479674100875854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.417169451713562},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4149458408355713},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4117073714733124},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4040203094482422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.269250750541687},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13665729761123657},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.09412533044815063}],"concepts":[{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7710158228874207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7055158019065857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6414833068847656},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.636214017868042},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4707042872905731},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4605265259742737},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.44768714904785156},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.44479674100875854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.417169451713562},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4149458408355713},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4117073714733124},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4040203094482422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.269250750541687},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13665729761123657},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.09412533044815063},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/15472450.2017.1305271","is_oa":false,"landing_page_url":"https://doi.org/10.1080/15472450.2017.1305271","pdf_url":null,"source":{"id":"https://openalex.org/S172631016","display_name":"Journal of Intelligent Transportation Systems","issn_l":"1547-2442","issn":["1547-2442","1547-2450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1500895378","https://openalex.org/W1504694836","https://openalex.org/W1570448133","https://openalex.org/W1577668191","https://openalex.org/W1680797894","https://openalex.org/W1932781435","https://openalex.org/W1974588631","https://openalex.org/W1997844571","https://openalex.org/W2004074287","https://openalex.org/W2005378233","https://openalex.org/W2013875843","https://openalex.org/W2026140901","https://openalex.org/W2036415539","https://openalex.org/W2037982005","https://openalex.org/W2040321327","https://openalex.org/W2043772506","https://openalex.org/W2043783848","https://openalex.org/W2073792037","https://openalex.org/W2078619499","https://openalex.org/W2084231748","https://openalex.org/W2095345875","https://openalex.org/W2100078453","https://openalex.org/W2100330570","https://openalex.org/W2110934250","https://openalex.org/W2112680570","https://openalex.org/W2119821739","https://openalex.org/W2122463117","https://openalex.org/W2123504579","https://openalex.org/W2128534087","https://openalex.org/W2136251662","https://openalex.org/W2138007066","https://openalex.org/W2139212933","https://openalex.org/W2147169507","https://openalex.org/W2149454242","https://openalex.org/W2153534417","https://openalex.org/W2154053567","https://openalex.org/W2158694395","https://openalex.org/W2220750102","https://openalex.org/W2410077615","https://openalex.org/W2442734498","https://openalex.org/W2503062631","https://openalex.org/W2543580944","https://openalex.org/W4230835027","https://openalex.org/W4244238212","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2071599417","https://openalex.org/W2048716406","https://openalex.org/W1870444468","https://openalex.org/W1964725559","https://openalex.org/W3109748140","https://openalex.org/W2045053268","https://openalex.org/W2433492094","https://openalex.org/W2767833206","https://openalex.org/W1556327589","https://openalex.org/W2108671564"],"abstract_inverted_index":{"Dangerous":[0],"driving":[1,50,108,128,187,226,244],"behavior":[2,51,109,188,227,245],"detection":[3,46,182,228],"can":[4,237],"be":[5,238],"used":[6,86,199],"in":[7,229,246],"video":[8,54,230,247],"surveillance":[9,231,248],"systems":[10],"to":[11,43,79,99,125,193,241],"identify":[12,126],"dangerous":[13,49,107,127,186,225,243],"patterns,":[14],"such":[15],"as":[16],"Abrupt":[17],"Double":[18],"Lane":[19],"Change":[20],"(ALC),":[21],"Retrograde":[22],"Driving":[23],"(RD),":[24],"and":[25,34,74,93,134,165,207],"Illegal":[26],"U-Turn":[27],"(IT),":[28],"for":[29,106,167,224],"traffic":[30,32],"design,":[31],"management,":[33],"law":[35],"enforcement.":[36],"The":[37,144],"purpose":[38],"of":[39,48,67,136,185,195],"this":[40],"study":[41],"is":[42,63,77,97,122,149,191],"develop":[44],"a":[45,57,84,113],"method":[47,59,89,218,236],"based":[52],"on":[53,175],"surveillance.":[55],"First,":[56],"novel":[58],"named":[60,90],"trajectory":[61,68,104,172,179],"histogram":[62,73],"proposed.":[64],"A":[65],"set":[66],"histograms":[69,105],"(e.g.,":[70],"control":[71],"points":[72],"velocity":[75],"histogram)":[76],"constructed":[78],"represent":[80],"vehicle":[81],"motion.":[82],"Then,":[83],"frequently":[85,198],"feature":[87],"selection":[88],"Minimum":[91],"Redundancy":[92],"Maximum":[94],"Relevance":[95],"(mRMR)":[96],"introduced":[98],"evaluate":[100],"the":[101,132,137,169,176,181,196,216,220,234],"most":[102,170,177,197],"representative":[103,153,171,178],"detection.":[110],"In":[111,211],"addition,":[112,212],"hybrid":[114],"algorithm,":[115],"Particle":[116],"Swarm":[117],"Optimization-Support":[118],"Vector":[119],"Machine":[120],"(PSO_SVM),":[121],"then":[123],"developed":[124],"behavior.":[129],"To":[130],"validate":[131],"performance":[133],"effectiveness":[135],"proposed":[138,217,235],"method,":[139],"several":[140],"experiments":[141],"are":[142],"conducted.":[143],"results":[145],"show":[146],"that":[147,215],"mRMR":[148],"better":[150],"than":[151],"other":[152],"methods,":[154],"namely":[155],"Conditional":[156],"Mutual":[157,161],"Information":[158,162],"Maximization":[159,163],"(CMIM),":[160],"(MIM),":[164],"ReliefF,":[166],"evaluating":[168],"histograms.":[173],"Based":[174],"histograms,":[180],"accuracy":[183],"rate":[184],"using":[189],"PSO_SVM":[190],"superior":[192],"those":[194],"classifiers\u2014Na\u00efve":[200],"Bayesian":[201],"Classifier":[202],"(NBC),":[203],"k-Nearest":[204],"Neighbor":[205],"(kNN),":[206],"C4.5":[208],"decision":[209],"tree.":[210],"we":[213],"find":[214],"outperforms":[219],"two":[221],"common":[222],"approaches":[223],"systems.":[232,249],"Therefore,":[233],"widely":[239],"applied":[240],"detect":[242]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}
