{"id":"https://openalex.org/W4389314709","doi":"https://doi.org/10.1145/3627377.3627437","title":"Deep learning based intersection multi-objective detection and congestion guidance","display_name":"Deep learning based intersection multi-objective detection and congestion guidance","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4389314709","doi":"https://doi.org/10.1145/3627377.3627437"},"language":"en","primary_location":{"id":"doi:10.1145/3627377.3627437","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627377.3627437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-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/A5102904352","display_name":"Zhiyuan Wang","orcid":"https://orcid.org/0009-0000-8003-5956"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyuan Wang","raw_affiliation_strings":["Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065029718","display_name":"Gang Zhao","orcid":"https://orcid.org/0009-0006-6895-4793"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhao","raw_affiliation_strings":["Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006524264","display_name":"G. Lu","orcid":"https://orcid.org/0009-0003-8227-1532"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozan Lu","raw_affiliation_strings":["Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102904352"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18569047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"384","last_page":"390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9908000230789185,"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"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7400554418563843},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7080420255661011},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.6814069747924805},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.677030622959137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5591299533843994},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.5557957291603088},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.5557048320770264},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.5349266529083252},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5257592797279358},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5228246450424194},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5191106796264648},{"id":"https://openalex.org/keywords/traffic-optimization","display_name":"Traffic optimization","score":0.48571476340293884},{"id":"https://openalex.org/keywords/network-congestion","display_name":"Network congestion","score":0.4379728138446808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3967534005641937},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.27227354049682617},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.20794212818145752},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17784404754638672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7400554418563843},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7080420255661011},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.6814069747924805},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.677030622959137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5591299533843994},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.5557957291603088},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.5557048320770264},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.5349266529083252},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5257592797279358},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5228246450424194},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5191106796264648},{"id":"https://openalex.org/C86266404","wikidata":"https://www.wikidata.org/wiki/Q7832512","display_name":"Traffic optimization","level":4,"score":0.48571476340293884},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.4379728138446808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3967534005641937},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.27227354049682617},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.20794212818145752},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17784404754638672},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627377.3627437","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627377.3627437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2007526069","https://openalex.org/W2099051099","https://openalex.org/W2099944060","https://openalex.org/W2116383749","https://openalex.org/W2131940298","https://openalex.org/W2809148419","https://openalex.org/W2901807041","https://openalex.org/W2997922319","https://openalex.org/W3125725535","https://openalex.org/W3206041734","https://openalex.org/W3206162504"],"related_works":["https://openalex.org/W2161957991","https://openalex.org/W3117279048","https://openalex.org/W2672046035","https://openalex.org/W2972320057","https://openalex.org/W2621233240","https://openalex.org/W2898775471","https://openalex.org/W2895639930","https://openalex.org/W2886720181","https://openalex.org/W2052510777","https://openalex.org/W4285174196"],"abstract_inverted_index":{"As":[0],"urban":[1],"traffic":[2,70,105,110,123,129,153,165,172,177,187,202],"congestion":[3,18,40,58,88,98,124],"is":[4],"becoming":[5],"more":[6,8,160,184],"and":[7,17,39,55,68,85,119,151,204,208],"prominent,":[9],"how":[10],"to":[11,45],"efficiently":[12],"perform":[13],"multiple":[14,50,76],"target":[15,51],"detection":[16,38,48,95],"guidance":[19,41,61],"at":[20,78,116],"intersections":[21,54,79,91],"has":[22,138],"become":[23],"an":[24],"important":[25],"research":[26],"direction.":[27],"In":[28],"this":[29,136],"paper,":[30],"we":[31],"propose":[32],"a":[33],"deep":[34,65,82],"learning-based":[35],"intersection":[36,57,118],"multi-target":[37],"method,":[42],"which":[43,158],"aims":[44],"achieve":[46],"accurate":[47],"of":[49,90,145,201],"vehicles":[52,115],"in":[53,135,155,210],"alleviate":[56],"through":[59],"intelligent":[60,69],"strategies":[62],"by":[63,80,107,168],"combining":[64],"learning":[66,83],"techniques":[67],"systems.":[71],"Specifically,":[72],"the":[73,87,94,100,104,109,117,122,132,139,143,163,171,176,194],"method":[74,133,195],"detects":[75],"targets":[77,154,203],"using":[81],"algorithms":[84],"calculates":[86],"index":[89],"based":[92],"on":[93],"results.":[96],"Under":[97],"conditions,":[99],"system":[101],"will":[102],"control":[103],"flow":[106,178],"varying":[108],"signal":[111,173],"duration,":[112],"thus":[113,183],"guiding":[114],"effectively":[120,185,197],"reducing":[121,186],"level.":[125],"Compared":[126],"with":[127],"traditional":[128],"management":[130],"methods,":[131],"proposed":[134],"paper":[137],"following":[140],"advantages:":[141],"first,":[142],"use":[144],"machine":[146],"vision":[147],"technology":[148],"can":[149,159,179,196],"monitor":[150],"identify":[152],"real":[156],"time,":[157],"accurately":[161],"reflect":[162],"actual":[164],"conditions;":[166],"second,":[167],"flexibly":[169],"adjusting":[170],"timing":[174],"length,":[175],"be":[180],"better":[181],"controlled,":[182],"congestion;":[188],"finally,":[189],"experimental":[190],"results":[191],"show":[192],"that":[193],"detect":[198],"many":[199],"types":[200],"shows":[205],"good":[206],"performance":[207],"robustness":[209],"practical":[211],"scenarios.":[212]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}