{"id":"https://openalex.org/W4408399563","doi":"https://doi.org/10.1109/tim.2025.3551031","title":"Pedestrian Trajectory Prediction Method Based on Feature Fusion","display_name":"Pedestrian Trajectory Prediction Method Based on Feature Fusion","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408399563","doi":"https://doi.org/10.1109/tim.2025.3551031"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3551031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3551031","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5103973934","display_name":"Tian Yang","orcid":"https://orcid.org/0000-0002-9667-1989"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Yang","raw_affiliation_strings":["Harbin Institute of Technology of China, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-9667-1989","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology of China, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720490","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0002-0641-8593"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["Harbin Institute of Technology of China, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-0641-8593","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology of China, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108314590","display_name":"Jian Lai","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Lai","raw_affiliation_strings":["Harbin Institute of Technology of China, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0001-8791-7019","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology of China, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100725760","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0001-9894-7478"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Harbin Institute of Technology of China, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9894-7478","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology of China, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2105,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.85445127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9114000201225281,"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":0.9114000201225281,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7903015613555908},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.692497193813324},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5847876667976379},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5630657076835632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5505764484405518},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.542450487613678},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5002634525299072},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4535475969314575},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39434945583343506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3517884910106659},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2709895968437195},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15840420126914978}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7903015613555908},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.692497193813324},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5847876667976379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5630657076835632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5505764484405518},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.542450487613678},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5002634525299072},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4535475969314575},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39434945583343506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3517884910106659},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2709895968437195},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15840420126914978},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3551031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3551031","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G4879600346","display_name":"\u536b\u661f-5G\u4e00\u4f53\u5316\u7f51\u7edc\u540c\u9891\u5e72\u6270\u673a\u7406\u5206\u6790\u53ca\u6d88\u9664\u65b9\u6cd5\u7814\u7a76","funder_award_id":"62071146","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":45,"referenced_works":["https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W2970989527","https://openalex.org/W2998687243","https://openalex.org/W3012055358","https://openalex.org/W3129176582","https://openalex.org/W3139491754","https://openalex.org/W3181125448","https://openalex.org/W3201466242","https://openalex.org/W3215772821","https://openalex.org/W4205732353","https://openalex.org/W4210543182","https://openalex.org/W4225828630","https://openalex.org/W4236596013","https://openalex.org/W4292994069","https://openalex.org/W4293149619","https://openalex.org/W4295845519","https://openalex.org/W4295934629","https://openalex.org/W4296311540","https://openalex.org/W4296400741","https://openalex.org/W4307404699","https://openalex.org/W4312447176","https://openalex.org/W4312506424","https://openalex.org/W4312638165","https://openalex.org/W4312720735","https://openalex.org/W4312750092","https://openalex.org/W4313041951","https://openalex.org/W4317772253","https://openalex.org/W4321021733","https://openalex.org/W4376566249","https://openalex.org/W4379378673","https://openalex.org/W4379622683","https://openalex.org/W4386071549","https://openalex.org/W4386857800","https://openalex.org/W4388430461","https://openalex.org/W4389987536","https://openalex.org/W4392737770","https://openalex.org/W4392826107","https://openalex.org/W4393946818","https://openalex.org/W4394707143","https://openalex.org/W4399439711","https://openalex.org/W4400487933","https://openalex.org/W4400520817","https://openalex.org/W4403095441","https://openalex.org/W4403598715"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W4205958986","https://openalex.org/W2197846993","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1,38,51,155,245],"prediction":[2,39,221,246],"has":[3],"broad":[4],"application":[5],"prospects":[6],"in":[7,32,116,137,210,244,249,264,272],"multiple":[8],"fields.":[9],"It":[10],"can":[11,165],"be":[12],"integrated":[13],"into":[14,192],"various":[15],"instruments":[16],"and":[17,23,49,73,100,104,127,159,169,219,269],"meters,":[18],"such":[19],"as":[20,26,28],"millimeter-wave":[21],"radars":[22],"LiDAR":[24],"devices,":[25],"well":[27],"camera":[29,43],"surveillance":[30],"equipment":[31],"intelligent":[33],"security":[34],"systems.":[35],"Currently,":[36],"many":[37],"methods":[40],"use":[41,225],"overhead":[42,152],"sensors":[44],"to":[45,68,90,121,146,205,230],"obtain":[46],"scene":[47,149],"information":[48,72,150,156,168,175,189],"historical":[50,154],"data.":[52,79],"But":[53],"they":[54],"also":[55,283],"have":[56],"some":[57,117],"shortcomings.":[58],"On":[59,80],"one":[60],"hand,":[61,83],"there":[62,84],"is":[63,85,203,282],"the":[64,75,81,86,93,96,101,124,142,177,188,193,197,207,211,214,237,254,257,278],"challenge":[65],"of":[66,88,157,196],"how":[67,89],"effectively":[69,284],"integrate":[70,147],"feature":[71,174],"capture":[74],"complex":[76,182,250],"interactions":[77,172],"between":[78,95],"other":[82],"issue":[87],"accurately":[91],"measure":[92,206],"difference":[94],"model\u2019s":[97,279],"predicted":[98],"values":[99,103],"actual":[102],"reduce":[105,166,213],"cumulative":[106],"errors":[107,216,261],"during":[108,217],"training.":[109],"The":[110],"commonly":[111],"used":[112],"concatenation":[113],"fusion":[114,144],"method":[115,145,164,259],"approaches":[118],"may":[119],"fail":[120],"fully":[122],"consider":[123],"intrinsic":[125],"correlations":[126],"differences":[128],"among":[129,173],"different":[130],"features,":[131],"simply":[132],"concatenating":[133],"them":[134],"together.":[135],"Therefore,":[136],"this":[138],"article,":[139],"we":[140,186,224],"adopt":[141],"average":[143,265],"static":[148],"from":[151],"cameras,":[153],"pedestrians,":[158],"social":[160],"interaction":[161],"information.":[162],"This":[163,199],"redundant":[167],"allow":[170],"implicit":[171],"within":[176],"model,":[178,212,256],"thereby":[179],"capturing":[180],"more":[181,232],"data":[183],"relationships.":[184],"Second,":[185],"embed":[187],"fractal":[190,200],"equation":[191],"loss":[194,201,209],"function":[195],"model.":[198],"term":[202],"designed":[204],"detail":[208],"accumulated":[215],"training,":[218],"enhance":[220],"accuracy.":[222],"Finally,":[223],"generative":[226],"adversarial":[227],"network":[228],"(GAN)":[229],"generate":[231],"realistic":[233],"trajectories.":[234],"Experiments":[235],"on":[236],"ETH/UCY":[238],"dataset":[239],"demonstrate":[240],"a":[241],"significant":[242],"improvement":[243],"accuracy,":[247],"particularly":[248],"situations.":[251],"Compared":[252],"with":[253],"baseline":[255],"proposed":[258],"reduces":[260],"by":[262,270],"14.8%":[263],"displacement":[266,274],"error":[267,275],"(ADE)":[268],"25.2%":[271],"final":[273],"(FDE).":[276],"Furthermore,":[277],"training":[280],"time":[281],"reduced.":[285]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}