{"id":"https://openalex.org/W4411725095","doi":"https://doi.org/10.1109/tits.2025.3580549","title":"A Data-Driven and Kinematics-Aware Approach to Reconstruct Full-Sample Vehicle Trajectories From Low-Quality Roadside Perception Data","display_name":"A Data-Driven and Kinematics-Aware Approach to Reconstruct Full-Sample Vehicle Trajectories From Low-Quality Roadside Perception Data","publication_year":2025,"publication_date":"2025-06-27","ids":{"openalex":"https://openalex.org/W4411725095","doi":"https://doi.org/10.1109/tits.2025.3580549"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3580549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3580549","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/A5013018459","display_name":"Zimu Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zimu Zeng","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-1468-4409","affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002189030","display_name":"Cong Zhao","orcid":"https://orcid.org/0000-0002-1017-9118"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Zhao","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1017-9118","affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025332837","display_name":"Shiyu Wang","orcid":"https://orcid.org/0009-0006-1898-1312"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyu Wang","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047463332","display_name":"Yuxiong Ji","orcid":"https://orcid.org/0000-0001-8554-0396"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiong Ji","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8554-0396","affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406988","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0002-4548-3697"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["Department of Information and Communication Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4548-3697","affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004514343","display_name":"Yuchuan Du","orcid":"https://orcid.org/0000-0002-8497-3402"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchuan Du","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8497-3402","affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5013018459"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":1.2198,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79696414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"26","issue":"10","first_page":"15041","last_page":"15054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9986000061035156,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.993399977684021,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9847000241279602,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.7424001693725586},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6893982887268066},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6388808488845825},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5787642002105713},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.5179702043533325},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4996323585510254},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4394480288028717},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4354991614818573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4302927851676941},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23197591304779053},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15676823258399963},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07159480452537537}],"concepts":[{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.7424001693725586},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6893982887268066},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6388808488845825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5787642002105713},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.5179702043533325},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4996323585510254},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4394480288028717},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4354991614818573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4302927851676941},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23197591304779053},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15676823258399963},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07159480452537537},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3580549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3580549","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":[{"score":0.47999998927116394,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2598416257","display_name":null,"funder_award_id":"24QA2709600","funder_id":"https://openalex.org/F4320327803","funder_display_name":"Shanghai Rising-Star Program"},{"id":"https://openalex.org/G2737399120","display_name":null,"funder_award_id":"52472352","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G351996751","display_name":null,"funder_award_id":"22120230311","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327803","display_name":"Shanghai Rising-Star Program","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W168785721","https://openalex.org/W2154844948","https://openalex.org/W2343568200","https://openalex.org/W2424778531","https://openalex.org/W2790715140","https://openalex.org/W2903782687","https://openalex.org/W2963906196","https://openalex.org/W2991653934","https://openalex.org/W3024068946","https://openalex.org/W3034734814","https://openalex.org/W3108486966","https://openalex.org/W3169575318","https://openalex.org/W3174686248","https://openalex.org/W3201859961","https://openalex.org/W3207981904","https://openalex.org/W3210701025","https://openalex.org/W4206209964","https://openalex.org/W4210389721","https://openalex.org/W4213100704","https://openalex.org/W4214701136","https://openalex.org/W4214895168","https://openalex.org/W4225976909","https://openalex.org/W4226444630","https://openalex.org/W4285082182","https://openalex.org/W4285161977","https://openalex.org/W4285212922","https://openalex.org/W4285244183","https://openalex.org/W4308044468","https://openalex.org/W4312939270","https://openalex.org/W4313316269","https://openalex.org/W4313583162","https://openalex.org/W4381332009","https://openalex.org/W4386076672","https://openalex.org/W4388562378","https://openalex.org/W4389593813","https://openalex.org/W4390492375","https://openalex.org/W4391341377","https://openalex.org/W4392939656","https://openalex.org/W4400016719","https://openalex.org/W4402816840","https://openalex.org/W4403936626"],"related_works":["https://openalex.org/W2789522126","https://openalex.org/W2066693961","https://openalex.org/W2368363778","https://openalex.org/W122584421","https://openalex.org/W4244295168","https://openalex.org/W2753351751","https://openalex.org/W3185180338","https://openalex.org/W2889348933","https://openalex.org/W2351643838","https://openalex.org/W3033677963"],"abstract_inverted_index":{"Full-sample":[0],"vehicle":[1,49,88,100],"trajectories":[2,96],"collected":[3],"by":[4],"roadside":[5],"sensors":[6],"are":[7],"pivotal":[8],"for":[9,46],"advancements":[10],"in":[11,115],"active":[12],"traffic":[13],"management":[14],"and":[15,22,29,43,69,135],"vehicle-highway":[16],"automation":[17],"applications.":[18,34],"However,":[19],"sensor":[20],"inefficiencies":[21],"environmental":[23],"factors":[24],"often":[25],"lead":[26],"to":[27,64,91,99],"incomplete":[28],"noisy":[30],"data,":[31],"impeding":[32],"practical":[33],"To":[35],"overcome":[36],"this":[37],"hurdle,":[38],"we":[39],"propose":[40],"a":[41,87],"data-driven":[42,58],"kinematics-aware":[44],"method":[45],"reconstructing":[47],"full-sample":[48],"trajectories.":[50],"It":[51],"employs":[52],"an":[53],"encoder-decoder":[54],"architecture,":[55],"where":[56],"the":[57,94,122],"encoder":[59],"utilizes":[60],"graph-based":[61],"map":[62],"modeling":[63],"capture":[65],"road":[66],"network":[67],"characteristics":[68],"models":[70],"multi-vehicle":[71],"interactions":[72],"based":[73],"on":[74,104,121],"real-world":[75],"driving":[76],"attention":[77],"patterns.":[78],"The":[79],"model-driven":[80],"decoder":[81],"integrates":[82],"conditional":[83],"variational":[84],"autoencoder":[85],"with":[86],"kinematic":[89,101],"model,":[90],"ensure":[92],"that":[93,109,126],"generated":[95],"adhere":[97],"closely":[98],"principles.":[102],"Experiments":[103],"large-scale":[105],"trajectory":[106,116,132],"datasets":[107],"demonstrate":[108],"our":[110,127],"approach":[111,128],"exhibits":[112],"good":[113],"performance":[114],"reconstruction.":[117],"Furthermore,":[118],"case":[119],"studies":[120],"DAIR-V2X":[123],"dataset":[124],"indicate":[125],"could":[129],"improve":[130],"raw":[131],"data":[133],"quality":[134],"downstream":[136],"prediction":[137],"accuracy.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}