{"id":"https://openalex.org/W4416749106","doi":"https://doi.org/10.1109/iros60139.2025.11246407","title":"PhysGCN-DL: Physics-Informed Graph Convolutional Networks with Diversity-Aware Loss Optimization for Multimodal Pedestrian Trajectory Prediction","display_name":"PhysGCN-DL: Physics-Informed Graph Convolutional Networks with Diversity-Aware Loss Optimization for Multimodal Pedestrian Trajectory Prediction","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749106","doi":"https://doi.org/10.1109/iros60139.2025.11246407"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5113354755","display_name":"Zihan Jiang","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":"Zihan Jiang","raw_affiliation_strings":["Tongji University,Shanghai Research Institute for Intelligent Autonomous Systems,Shanghai,P.R. China,200000"],"affiliations":[{"raw_affiliation_string":"Tongji University,Shanghai Research Institute for Intelligent Autonomous Systems,Shanghai,P.R. China,200000","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728390","display_name":"Ruonan Liu","orcid":"https://orcid.org/0000-0001-9963-7092"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruonan Liu","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077971774","display_name":"Ying Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Zhou","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064406652","display_name":"Haibo Lu","orcid":"https://orcid.org/0000-0002-7161-1146"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibo Lu","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,P.R. China,518000"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,P.R. China,518000","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009872730","display_name":"Boyuan Yang","orcid":"https://orcid.org/0000-0002-5248-0929"},"institutions":[{"id":"https://openalex.org/I4210125878","display_name":"Suzhou Research Institute","ror":"https://ror.org/03ebk0c60","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210125878"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"BoYuan Yang","raw_affiliation_strings":["Nanjing University,Center for Advanced Control and Smart Operations,Suzhou,P.R. China,215163"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Center for Advanced Control and Smart Operations,Suzhou,P.R. China,215163","institution_ids":["https://openalex.org/I4210125878"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101438448","display_name":"Di Lin","orcid":"https://orcid.org/0000-0002-9324-800X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Lin","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,P.R. China,300000"],"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,P.R. China,300000","institution_ids":["https://openalex.org/I162868743","https://openalex.org/I132369690"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100428753","display_name":"Weidong Zhang","orcid":"https://orcid.org/0000-0003-0016-0402"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,School of Automation and Intelligent Sensing,Shanghai,P.R. China,200240","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5113354755"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39002227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"38","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9038000106811523,"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":0.9038000106811523,"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":0.00989999994635582,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.009100000374019146,"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/interpretability","display_name":"Interpretability","score":0.8431000113487244},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.792900025844574},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6110000014305115},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4887000024318695},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4724999964237213},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.36070001125335693}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8431000113487244},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.792900025844574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728999853134155},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6110000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5533999800682068},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.516700029373169},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3605000078678131},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C161677786","wikidata":"https://www.wikidata.org/wiki/Q2478475","display_name":"Neighbourhood (mathematics)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1571268436","https://openalex.org/W1970206276","https://openalex.org/W2167052694","https://openalex.org/W2424778531","https://openalex.org/W2807456624","https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W3000378996","https://openalex.org/W3035096461","https://openalex.org/W3104079458","https://openalex.org/W3205125897","https://openalex.org/W3213801837","https://openalex.org/W3217210982","https://openalex.org/W4210529447","https://openalex.org/W4225973697","https://openalex.org/W4285130296","https://openalex.org/W4291653124","https://openalex.org/W4310983610","https://openalex.org/W4323519357","https://openalex.org/W4362689457","https://openalex.org/W4366150181","https://openalex.org/W4380372542","https://openalex.org/W4389987536","https://openalex.org/W4390097157","https://openalex.org/W4391092980","https://openalex.org/W4391341377","https://openalex.org/W4391468021","https://openalex.org/W4391759873","https://openalex.org/W4391992314","https://openalex.org/W4393946714","https://openalex.org/W4396817341","https://openalex.org/W4396910051","https://openalex.org/W4398226264","https://openalex.org/W4400228460","https://openalex.org/W4400487853","https://openalex.org/W4401972311","https://openalex.org/W4402830181","https://openalex.org/W4402892200","https://openalex.org/W4403635664","https://openalex.org/W4403791659","https://openalex.org/W4405778634","https://openalex.org/W4405785268","https://openalex.org/W4405785378","https://openalex.org/W4405785464","https://openalex.org/W4409261950","https://openalex.org/W4410949756","https://openalex.org/W4415800582"],"related_works":[],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1],"prediction":[2,91],"ensures":[3],"safe":[4],"navigation":[5],"in":[6,22,63,115],"autonomous":[7],"driving":[8],"and":[9,28,74,93,103,118],"intelligent":[10],"robots.":[11],"Existing":[12],"methods":[13,114],"have":[14],"shown":[15],"promising":[16],"results":[17],"but":[18],"still":[19],"face":[20],"challenges":[21],"handling":[23],"dynamic":[24,51],"environments,":[25],"social":[26,79],"interactions,":[27],"high-dimensional":[29],"data.":[30],"In":[31],"this":[32],"paper,":[33],"we":[34,82],"propose":[35],"a":[36,84],"novel":[37,85],"PhysGCN-DL":[38],"within":[39],"the":[40,69,76,97],"itransformer":[41],"framework":[42],"to":[43,88],"address":[44],"these":[45],"challenges.":[46],"Our":[47],"model":[48],"incorporates":[49],"physically-inspired":[50],"interaction":[52],"modeling":[53],"by":[54],"representing":[55],"physical":[56],"interactions":[57],"between":[58],"pedestrians":[59],"as":[60],"edge":[61],"weights":[62],"graph":[64],"convolution.":[65],"This":[66],"approach":[67,111],"captures":[68],"heterogeneity":[70],"of":[71,78],"pedestrian":[72,120],"movement":[73],"improves":[75],"interpretability":[77],"interactions.":[80],"Moreover,":[81],"design":[83],"loss":[86],"function":[87],"jointly":[89],"enhance":[90],"diversity":[92],"accuracy,":[94],"thereby":[95],"improving":[96],"model\u2019s":[98],"robustness":[99],"across":[100],"both":[101],"dense":[102],"sparse":[104],"scenarios.":[105],"Empirical":[106],"evaluations":[107],"confirm":[108],"that":[109],"our":[110],"outperforms":[112],"existing":[113],"generating":[116],"accurate":[117],"diverse":[119],"trajectories.":[121]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}