{"id":"https://openalex.org/W3168080791","doi":"https://doi.org/10.1109/tiv.2022.3149624","title":"Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users\u2019 Trajectories","display_name":"Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users\u2019 Trajectories","publication_year":2022,"publication_date":"2022-02-08","ids":{"openalex":"https://openalex.org/W3168080791","doi":"https://doi.org/10.1109/tiv.2022.3149624","mag":"3168080791"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2022.3149624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3149624","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","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/A5016665121","display_name":"Viktor Kre\u00df","orcid":"https://orcid.org/0000-0002-9314-2424"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Viktor Kress","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9314-2424","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090425661","display_name":"Fabian Jeske","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Jeske","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086864323","display_name":"Stefan Zernetsch","orcid":"https://orcid.org/0000-0003-2016-5059"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Zernetsch","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2016-5059","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047844917","display_name":"Konrad Doll","orcid":"https://orcid.org/0000-0002-3746-2319"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konrad Doll","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3746-2319","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffen- burg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065340030","display_name":"Bernhard Sick","orcid":"https://orcid.org/0000-0001-9467-656X"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Sick","raw_affiliation_strings":["Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9467-656X","affiliations":[{"raw_affiliation_string":"Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7056,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.66140673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"8","issue":"3","first_page":"2592","last_page":"2603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9972000122070312,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9900000095367432,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.6955388188362122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6884267330169678},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6141470074653625},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5731222629547119},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5375840663909912},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.49434995651245117},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42350322008132935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3871912658214569},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17492473125457764},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16165313124656677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14106088876724243}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6955388188362122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6884267330169678},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6141470074653625},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5731222629547119},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5375840663909912},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.49434995651245117},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42350322008132935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3871912658214569},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17492473125457764},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16165313124656677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14106088876724243},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2022.3149624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3149624","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","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":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G8599740047","display_name":null,"funder_award_id":"SPP 1835","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1579853615","https://openalex.org/W1901129140","https://openalex.org/W2004641798","https://openalex.org/W2047634553","https://openalex.org/W2064675550","https://openalex.org/W2254249950","https://openalex.org/W2424778531","https://openalex.org/W2558580397","https://openalex.org/W2559085405","https://openalex.org/W2583585015","https://openalex.org/W2626967530","https://openalex.org/W2787794795","https://openalex.org/W2801667201","https://openalex.org/W2807456624","https://openalex.org/W2890685830","https://openalex.org/W2897623894","https://openalex.org/W2914521909","https://openalex.org/W2962783540","https://openalex.org/W2963001155","https://openalex.org/W2964121744","https://openalex.org/W2970683415","https://openalex.org/W2971292066","https://openalex.org/W3007298738","https://openalex.org/W3007675788","https://openalex.org/W3010003086","https://openalex.org/W3029177463","https://openalex.org/W3035339264","https://openalex.org/W3092107260","https://openalex.org/W3114948913","https://openalex.org/W4393785059","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6634817459","https://openalex.org/W6639824700","https://openalex.org/W6691692454","https://openalex.org/W6739651123","https://openalex.org/W6769377150","https://openalex.org/W6783858723","https://openalex.org/W6863066940"],"related_works":["https://openalex.org/W2383807498","https://openalex.org/W1978572805","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2149980199","https://openalex.org/W2019977573","https://openalex.org/W2009776842","https://openalex.org/W1935138604"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"an":[3],"approach":[4,137],"for":[5,85],"probabilistic":[6],"trajectory":[7],"forecasting":[8],"of":[9,37,49,56,62,76,104,121,161,172],"vulnerable":[10],"road":[11],"users":[12],"(VRUs)":[13],"is":[14,44,138,179],"presented,":[15],"taking":[16],"into":[17],"consideration":[18],"past":[19],"movements":[20,26,36],"and":[21,35,59,72,89,108,114,123,169],"the":[22,33,47,54,60,70,74,102,119,145,153,159,162,166],"surrounding":[23,42],"environment.":[24],"Past":[25],"are":[27,65,83],"represented":[28],"by":[29],"3D":[30,146],"poses":[31,122,147],"reflecting":[32],"posture":[34],"individual":[38,167],"body":[39],"parts.":[40],"The":[41,81,155,192],"environment":[43],"modeled":[45],"in":[46,67,73,101,185],"form":[48,75,103],"semantic":[50,124,156],"maps":[51,157],"showing,":[52],"e.g.,":[53],"course":[55],"streets,":[57],"sidewalks,":[58],"occurrence":[61],"obstacles.":[63,176],"Forecasts":[64],"generated":[66],"grids":[68],"discretizing":[69],"space":[71],"arbitrary":[77],"discrete":[78],"probability":[79,106,163],"distributions.":[80],"distributions":[82,164],"evaluated":[84,180],"their":[86,111],"reliability,":[87],"sharpness,":[88],"positional":[90],"accuracy.":[91],"We":[92,116],"compare":[93],"our":[94,136],"method":[95,178],"with":[96],"two":[97],"approaches":[98],"providing":[99],"forecasts":[100,171],"continuous":[105],"distributions,":[107],"we":[109,129],"discuss":[110],"respective":[112],"advantages":[113],"disadvantages.":[115],"thereby":[117],"investigate":[118],"impact":[120,151],"maps.":[125],"Using":[126],"a":[127,149,182,189],"technique":[128],"refer":[130],"to":[131,140,165],"as":[132],"spatial":[133],"label":[134],"smoothing,":[135],"able":[139],"achieve":[141],"reliable":[142],"forecasts.":[143,154],"Overall,":[144],"have":[148],"positive":[150],"on":[152,181],"facilitate":[158],"adaptation":[160],"situation":[168],"prevent":[170],"trajectories":[173],"leading":[174],"through":[175],"Our":[177],"dataset":[183,193],"recorded":[184],"inner-city":[186],"traffic":[187],"using":[188],"research":[190],"vehicle.":[191],"has":[194],"been":[195],"made":[196],"publicly":[197],"available.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
