{"id":"https://openalex.org/W7150992293","doi":"https://doi.org/10.1109/tce.2026.3681333","title":"CVLS-ST: A Cross-View Long-Short Framework for Traffic Risk Prediction in Intelligent Urban Transportation Systems","display_name":"CVLS-ST: A Cross-View Long-Short Framework for Traffic Risk Prediction in Intelligent Urban Transportation Systems","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7150992293","doi":"https://doi.org/10.1109/tce.2026.3681333"},"language":null,"primary_location":{"id":"doi:10.1109/tce.2026.3681333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2026.3681333","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","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/A5032004495","display_name":"Yachao Yuan","orcid":"https://orcid.org/0000-0001-7498-002X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yachao Yuan","raw_affiliation_strings":["School of Future Science and Engineering and the Key Laboratory of General Artificial Intelligence and Large Models in Provincial Universities, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0001-7498-002X","affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering and the Key Laboratory of General Artificial Intelligence and Large Models in Provincial Universities, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xingyu Chen","orcid":"https://orcid.org/0009-0001-8495-8704"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyu Chen","raw_affiliation_strings":["School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0001-8495-8704","affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111247568","display_name":"Zixiang Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixiang Peng","raw_affiliation_strings":["School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065081670","display_name":"Mingdong Li","orcid":"https://orcid.org/0000-0001-8186-6735"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muting Li","raw_affiliation_strings":["School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133053215","display_name":"Zhen Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Yu","raw_affiliation_strings":["School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0003-9510-1727","affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081478770","display_name":"Yingwen Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingwen Wu","raw_affiliation_strings":["School of Future Science and Engineering and the Key Laboratory of General Artificial Intelligence and Large Models in Provincial Universities, Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0008-9131-9995","affiliations":[{"raw_affiliation_string":"School of Future Science and Engineering and the Key Laboratory of General Artificial Intelligence and Large Models in Provincial Universities, Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065487579","display_name":"Thar Baker","orcid":"https://orcid.org/0000-0002-5166-4873"},"institutions":[{"id":"https://openalex.org/I29891158","display_name":"University of Sharjah","ror":"https://ror.org/00engpz63","country_code":"AE","type":"education","lineage":["https://openalex.org/I29891158"]},{"id":"https://openalex.org/I4405259941","display_name":"University of Khorfakkan","ror":"https://ror.org/02yvzq394","country_code":"AE","type":"education","lineage":["https://openalex.org/I4405259941"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Thar Baker","raw_affiliation_strings":["College of Computing and Intelligent Systems, University of Khorfakkan, Sharjah, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0002-5166-4873","affiliations":[{"raw_affiliation_string":"College of Computing and Intelligent Systems, University of Khorfakkan, Sharjah, United Arab Emirates","institution_ids":["https://openalex.org/I29891158","https://openalex.org/I4405259941"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33502932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"72","issue":"2","first_page":"2930","last_page":"2942"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.6669999957084656,"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":0.6669999957084656,"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/T12127","display_name":"Software System Performance and Reliability","score":0.016300000250339508,"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"}},{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.013000000268220901,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.538100004196167},{"id":"https://openalex.org/keywords/advanced-traffic-management-system","display_name":"Advanced Traffic Management System","score":0.36629998683929443},{"id":"https://openalex.org/keywords/rail-transportation","display_name":"Rail transportation","score":0.3319999873638153},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.28619998693466187},{"id":"https://openalex.org/keywords/road-traffic","display_name":"Road traffic","score":0.2825999855995178},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2791999876499176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5799999833106995},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.538100004196167},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4244000017642975},{"id":"https://openalex.org/C42693407","wikidata":"https://www.wikidata.org/wiki/Q4686317","display_name":"Advanced Traffic Management System","level":3,"score":0.36629998683929443},{"id":"https://openalex.org/C2984780852","wikidata":"https://www.wikidata.org/wiki/Q3565868","display_name":"Rail transportation","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C56397880","wikidata":"https://www.wikidata.org/wiki/Q6044094","display_name":"Intelligent decision support system","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27639999985694885},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2694999873638153},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.263700008392334},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C2986452759","wikidata":"https://www.wikidata.org/wiki/Q7142599","display_name":"Rail traffic","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2026.3681333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2026.3681333","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7975650429725647}],"awards":[{"id":"https://openalex.org/G2264344241","display_name":"\u57fa\u4e8e\u7ebf\u6027\u7f16\u7801\u7684\u5b89\u5168\u9ad8\u6548\u8fb9\u7f18\u534f\u540c\u8ba1\u7b97\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"62072321","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4789407770","display_name":null,"funder_award_id":"62406215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6030937846","display_name":null,"funder_award_id":"72402156","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,52,80,99,122],"cornerstone":[2],"of":[3,136,149],"smart":[4],"city":[5],"consumer":[6],"ecosystems,":[7],"accurate":[8],"traffic":[9,59,74,137],"accident":[10],"risk":[11,35,60,75],"prediction":[12],"is":[13],"vital":[14],"for":[15,58],"proactive":[16],"safety":[17],"services":[18],"in":[19,165],"intelligent":[20],"transportation":[21],"systems.":[22],"However,":[23],"current":[24],"solutions":[25],"often":[26],"fail":[27],"to":[28,69,85,110,125],"integrate":[29],"heterogeneous":[30],"relational":[31,94],"features":[32],"(e.g.,":[33],"historical":[34],"correlations)":[36],"or":[37],"effectively":[38,86,111],"balance":[39],"long-term":[40,131],"periodic":[41],"patterns":[42],"with":[43],"transient":[44],"dynamics.":[45],"To":[46],"address":[47],"these":[48],"issues,":[49],"we":[50,78,97,120],"introduce":[51,121],"Cross-View":[53],"Long-Short":[54],"Spatial-Temporal":[55],"Framework":[56],"(CVLS-ST)":[57],"prediction,":[61],"which":[62],"innovatively":[63],"decouples":[64],"long-":[65],"and":[66,89,116,127,133,158],"short-term":[67,134],"dependencies":[68],"achieve":[70],"more":[71],"precise":[72],"urban":[73,167],"prediction.":[76],"Specifically,":[77],"design":[79],"cross-view":[81],"attention":[82],"graph":[83],"network":[84],"capture":[87,112],"complex":[88,166],"diverse":[90],"interactions":[91],"across":[92],"multiple":[93],"graphs.":[95],"Besides,":[96],"develop":[98],"Mamba":[100],"block":[101],"that":[102,146],"incorporates":[103],"state-space":[104],"modeling":[105],"into":[106],"LSTM\u2019s":[107],"gating":[108],"architecture":[109],"global":[113],"spatial":[114],"semantics":[115],"temporal":[117],"dependencies.":[118],"Moreover,":[119],"state-inherited":[123],"strategy":[124],"jointly":[126],"accurately":[128],"model":[129],"the":[130,147,152],"trends":[132],"dynamics":[135],"risk.":[138],"Extensive":[139],"experiments":[140],"on":[141,156,160],"two":[142],"real-world":[143],"datasets":[144],"show":[145],"F1-score":[148],"CVLS-ST":[150],"outperforms":[151],"state-of-the-art":[153],"by":[154],"20.37%":[155],"CHI":[157],"5.83%":[159],"NYC,":[161],"validating":[162],"its":[163],"effectiveness":[164],"environments.":[168]},"counts_by_year":[],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2026-04-07T00:00:00"}
