{"id":"https://openalex.org/W4392309242","doi":"https://doi.org/10.1109/jiot.2024.3371482","title":"Toward Efficient Traffic Incident Detection via Explicit Edge-Level Incident Modeling","display_name":"Toward Efficient Traffic Incident Detection via Explicit Edge-Level Incident Modeling","publication_year":2024,"publication_date":"2024-02-29","ids":{"openalex":"https://openalex.org/W4392309242","doi":"https://doi.org/10.1109/jiot.2024.3371482"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3371482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3371482","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5100322200","display_name":"Chen Liu","orcid":"https://orcid.org/0000-0003-1558-6836"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Liu","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726041","display_name":"Jiming Chen","orcid":"https://orcid.org/0000-0003-3155-3145"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiming Chen","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067320802","display_name":"Haoyu Liu","orcid":"https://orcid.org/0000-0002-8998-1217"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]},{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Liu","raw_affiliation_strings":["NetEase Fuxi AI Lab, Hangzhou, China","State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","Fuxi AI Lab, NetEase Games, Hangzhou"],"affiliations":[{"raw_affiliation_string":"NetEase Fuxi AI Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210091137"]},{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]},{"raw_affiliation_string":"Fuxi AI Lab, NetEase Games, Hangzhou","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102015526","display_name":"Shizhong Li","orcid":"https://orcid.org/0000-0003-4429-3549"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shizhong Li","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068195118","display_name":"Shibo He","orcid":"https://orcid.org/0000-0002-1505-6766"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibo He","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100322200"],"corresponding_institution_ids":["https://openalex.org/I4391767838"],"apc_list":null,"apc_paid":null,"fwci":1.4488,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83259628,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"11","first_page":"20015","last_page":"20029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8380957245826721},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5929099321365356},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5794798731803894},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5471632480621338},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4718359112739563},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4669543206691742},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.45712748169898987},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41295063495635986},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.41254541277885437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3126630187034607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.25235652923583984},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08573529124259949}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8380957245826721},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5929099321365356},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5794798731803894},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5471632480621338},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4718359112739563},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4669543206691742},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.45712748169898987},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41295063495635986},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.41254541277885437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3126630187034607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25235652923583984},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08573529124259949},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3371482","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3371482","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3506032873","display_name":null,"funder_award_id":"U23A20326","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1991574184","https://openalex.org/W2042759501","https://openalex.org/W2058898885","https://openalex.org/W2127735975","https://openalex.org/W2150263714","https://openalex.org/W2464164019","https://openalex.org/W2547208782","https://openalex.org/W2565239705","https://openalex.org/W2794774115","https://openalex.org/W2795138333","https://openalex.org/W2873671808","https://openalex.org/W2903797436","https://openalex.org/W2909550475","https://openalex.org/W2911535719","https://openalex.org/W2942843559","https://openalex.org/W2944250323","https://openalex.org/W2945996535","https://openalex.org/W2963358464","https://openalex.org/W2965341826","https://openalex.org/W2966587068","https://openalex.org/W2971381425","https://openalex.org/W2983576094","https://openalex.org/W2996705655","https://openalex.org/W2998336824","https://openalex.org/W3015799890","https://openalex.org/W3023128419","https://openalex.org/W3030935614","https://openalex.org/W3036417315","https://openalex.org/W3040221354","https://openalex.org/W3080758937","https://openalex.org/W3080948845","https://openalex.org/W3081497074","https://openalex.org/W3091193567","https://openalex.org/W3092962336","https://openalex.org/W3093759913","https://openalex.org/W3094246578","https://openalex.org/W3102730661","https://openalex.org/W3113826484","https://openalex.org/W3126525704","https://openalex.org/W3175500462","https://openalex.org/W3177236396","https://openalex.org/W3184084836","https://openalex.org/W4206503836","https://openalex.org/W4225512856","https://openalex.org/W4285210148","https://openalex.org/W4292186443","https://openalex.org/W4318953583","https://openalex.org/W6746015598","https://openalex.org/W6762924995","https://openalex.org/W6765581236","https://openalex.org/W6784081243"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866"],"abstract_inverted_index":{"Traffic":[0],"incident":[1],"detection":[2,181],"is":[3,82,108,127,186],"a":[4,120,130],"critical":[5],"task":[6],"within":[7,45],"traffic":[8,26,101,117],"monitoring":[9],"systems,":[10],"enabling":[11],"on-the-fly":[12],"alerts":[13],"for":[14,176,225],"emergency":[15],"actions.":[16],"Numerous":[17],"efforts":[18],"have":[19],"been":[20],"made":[21],"to":[22,66,84,132],"detect":[23,67,91],"and":[24,49,90,105,154,166,178,196,219],"localize":[25],"incidents":[27,42,71],"using":[28],"data":[29],"recorded":[30],"by":[31,119],"inductive":[32],"loop":[33],"detectors.":[34],"However,":[35],"they":[36],"only":[37],"focus":[38],"on":[39,74,189],"the":[40,46,51,75,87,116,124,134,147,171,204,231,234],"node-level":[41,177],"that":[43,54],"happen":[44],"surveillance":[47],"areas":[48],"ignore":[50],"edge-level":[52,179,226],"ones":[53],"take":[55],"place":[56],"outside":[57],"of":[58,70,94,210,233],"these":[59],"areas.":[60],"In":[61,110],"this":[62,92,111],"paper,":[63,112],"we":[64,113,138],"propose":[65,139],"both":[68,208],"kinds":[69,209],"simultaneously":[72],"based":[73,188],"sparsely":[76],"distributed":[77],"sensors.":[78],"An":[79],"important":[80],"challenge":[81],"how":[83],"explicitly":[85],"model":[86],"edge":[88],"status":[89],"kind":[93],"incidents.":[95],"Additionally,":[96],"capturing":[97],"complex":[98],"relationships":[99],"among":[100],"dynamics,":[102],"road":[103],"locations,":[104],"temporal":[106,164],"information":[107],"non-trivial.":[109],"first":[114],"describe":[115],"dynamics":[118],"fine-grained":[121],"graph":[122],"where":[123,146],"sensor":[125],"range":[126],"designed":[128],"as":[129],"hyper-parameter":[131],"control":[133],"coverage":[135],"boundaries.":[136],"Then,":[137],"an":[140],"Edge-and":[141],"Node-aware":[142],"Dual":[143],"AutoEncoder":[144],"(ENDAE),":[145],"correlations":[148],"are":[149,158,174],"decoupled":[150],"into":[151],"inter-nodes,":[152],"inter-series":[153],"inter-attribute":[155],"parts,":[156],"which":[157],"further":[159],"captured":[160],"via":[161],"node":[162],"encoder,":[163,168],"encoder":[165],"attribute":[167],"respectively.":[169],"Furthermore,":[170],"reconstruction":[172],"errors":[173],"calculated":[175],"event":[180],"separately.":[182],"The":[183],"overall":[184],"method":[185,206],"evaluated":[187],"two":[190],"real-world":[191],"datasets":[192],"from":[193],"Bay":[194],"Area":[195],"Los":[197],"Angeles":[198],"in":[199,207,217,222],"California.":[200],"ENDAE":[201,228],"surpasses":[202],"all":[203],"state-of-the-art":[205],"incidents,":[211,227],"with":[212],"at":[213],"least":[214],"12.5%":[215],"improvement":[216],"recall":[218,232],"18.5%":[220],"decrease":[221],"delay.":[223],"Notably,":[224],"achieves":[229],"double":[230],"previous":[235],"SOTA":[236],"methods.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}