{"id":"https://openalex.org/W4390097157","doi":"https://doi.org/10.1109/tie.2023.3342301","title":"A Unified Framework for Pedestrian Trajectory Prediction and Social-Friendly Navigation","display_name":"A Unified Framework for Pedestrian Trajectory Prediction and Social-Friendly Navigation","publication_year":2023,"publication_date":"2023-12-22","ids":{"openalex":"https://openalex.org/W4390097157","doi":"https://doi.org/10.1109/tie.2023.3342301"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2023.3342301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2023.3342301","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial 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/A5100386863","display_name":"Fang Fang","orcid":"https://orcid.org/0000-0002-5445-0766"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Fang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5445-0766","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021556528","display_name":"Xiangkai Wang","orcid":"https://orcid.org/0000-0001-5770-5464"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangkai Wang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-5770-5464","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102768416","display_name":"Zicong Li","orcid":"https://orcid.org/0009-0004-3151-9742"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zicong Li","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0004-3151-9742","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083546491","display_name":"Kun Qian","orcid":"https://orcid.org/0000-0001-7429-1742"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Qian","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-7429-1742","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101808587","display_name":"Bo Zhou","orcid":"https://orcid.org/0000-0002-3908-7575"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhou","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3908-7575","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.7533,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.69336224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"71","issue":"9","first_page":"11072","last_page":"11082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"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":0.9965999722480774,"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/pedestrian","display_name":"Pedestrian","score":0.8024705648422241},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7355815172195435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.589289665222168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33004045486450195},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32900887727737427},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26594993472099304},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.25345444679260254},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10208427906036377}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8024705648422241},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7355815172195435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.589289665222168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33004045486450195},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32900887727737427},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26594993472099304},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.25345444679260254},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10208427906036377},{"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/tie.2023.3342301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2023.3342301","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G729297588","display_name":null,"funder_award_id":"62073075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8499166613","display_name":"\u6784\u4ef6\u5316\u673a\u5668\u4eba\u7cfb\u7edf\u52a8\u6001\u4efb\u52a1\u89c4\u5212\u4e0e\u6267\u884c\u673a\u5236\u7814\u7a76","funder_award_id":"61573100","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1571268436","https://openalex.org/W1965311879","https://openalex.org/W1992225177","https://openalex.org/W2000365432","https://openalex.org/W2010236945","https://openalex.org/W2020209171","https://openalex.org/W2026938276","https://openalex.org/W2046213647","https://openalex.org/W2059993653","https://openalex.org/W2067589702","https://openalex.org/W2082585576","https://openalex.org/W2089584121","https://openalex.org/W2122381532","https://openalex.org/W2167052694","https://openalex.org/W2267107524","https://openalex.org/W2341150500","https://openalex.org/W2424778531","https://openalex.org/W2470964598","https://openalex.org/W2604372349","https://openalex.org/W2757579011","https://openalex.org/W2801667201","https://openalex.org/W2897983179","https://openalex.org/W2898910301","https://openalex.org/W2963001155","https://openalex.org/W2963353290","https://openalex.org/W2969294606","https://openalex.org/W2979724617","https://openalex.org/W2982242659","https://openalex.org/W2990646518","https://openalex.org/W2996500965","https://openalex.org/W3003480646","https://openalex.org/W3047385447","https://openalex.org/W3090345358","https://openalex.org/W3091067209","https://openalex.org/W3101693694","https://openalex.org/W3129678734","https://openalex.org/W4236309383","https://openalex.org/W4312788080","https://openalex.org/W4383108586","https://openalex.org/W4383109004","https://openalex.org/W6676264864","https://openalex.org/W6677648701"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W3122828758","https://openalex.org/W2170799233"],"abstract_inverted_index":{"In":[0,82],"recent":[1],"years,":[2],"stable":[3],"robot":[4,33],"navigation":[5,34,49,157,161],"systems":[6],"need":[7],"to":[8,46,98,134],"meet":[9],"the":[10,31,37,48,52,136,151,165],"requirements":[11],"of":[12,54,138,169],"comfort":[13,166],"and":[14,27,44,65,78,87,110,121,163,167],"sociality,":[15],"such":[16],"as":[17,42],"maintaining":[18],"an":[19,108],"appropriate":[20],"distance":[21],"from":[22],"pedestrians,":[23],"avoiding":[24],"crossing":[25],"crowds,":[26],"so":[28],"on.":[29],"However,":[30],"traditional":[32,152],"frameworks":[35],"treat":[36],"surrounding":[38],"pedestrians":[39,89],"or":[40],"objects":[41],"obstacles":[43],"fail":[45],"solve":[47],"problems":[50],"in":[51,141],"context":[53],"human-robot":[55],"interaction.":[56],"Therefore,":[57],"we":[58,85,106],"propose":[59,107],"a":[60,128],"unified":[61],"framework":[62,158],"for":[63],"human-aware":[64],"social-friendly":[66,156],"navigation,":[67],"which":[68],"includes":[69],"three":[70],"modules:":[71],"1)":[72],"pedestrian":[73,103],"modeling,":[74],"2)":[75],"trajectory":[76,104],"prediction,":[77,105],"3)":[79],"path":[80,126,153],"planning.":[81],"this":[83],"work,":[84],"detect":[86],"model":[88],"with":[90,150],"asymmetric":[91],"Gaussian":[92],"function,":[93],"while":[94],"introducing":[95],"motion-consistent":[96],"feature":[97,118],"identify":[99],"movement":[100],"group.":[101],"For":[102,125],"efficient":[109],"accurate":[111],"generative":[112],"adversarial":[113],"network":[114],"model,":[115],"combining":[116],"social":[117,170],"attention":[119],"mechanism,":[120],"variable":[122],"intention":[123],"filter.":[124],"planning,":[127,154],"\u201cplan-prediction-execution\u201d":[129],"cycle":[130],"mode":[131],"is":[132],"applied":[133],"improve":[135],"performance":[137],"mobile":[139],"robots":[140],"dynamic":[142],"environments.":[143],"The":[144],"experimental":[145],"results":[146],"show":[147],"that":[148],"compared":[149],"our":[155],"has":[159],"higher":[160],"efficiency":[162],"meets":[164],"sociality":[168],"navigation.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
