{"id":"https://openalex.org/W2565986202","doi":"https://doi.org/10.1109/itsc.2016.7795975","title":"A data-driven approach for pedestrian intention estimation","display_name":"A data-driven approach for pedestrian intention estimation","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2565986202","doi":"https://doi.org/10.1109/itsc.2016.7795975","mag":"2565986202"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2016.7795975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5057378607","display_name":"Benjamin V\u00f6lz","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benjamin Volz","raw_affiliation_strings":["Corporate Research, Robert Bosch GmbH, Renningen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corporate Research, Robert Bosch GmbH, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012194742","display_name":"Karsten Behrendt","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099960","display_name":"Systems Control (United States)","ror":"https://ror.org/014tted12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210099960"]},{"id":"https://openalex.org/I4210120115","display_name":"Robert Bosch (United States)","ror":"https://ror.org/02venad53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120115","https://openalex.org/I889804353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karsten Behrendt","raw_affiliation_strings":["Chassis Systems Control, Robert Bosch LLC, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chassis Systems Control, Robert Bosch LLC, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210099960","https://openalex.org/I4210120115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111996493","display_name":"Holger Mielenz","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Holger Mielenz","raw_affiliation_strings":["Corporate Research, Robert Bosch GmbH, Renningen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corporate Research, Robert Bosch GmbH, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078356081","display_name":"Igor Gilitschenski","orcid":"https://orcid.org/0000-0001-6426-365X"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Igor Gilitschenski","raw_affiliation_strings":["Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083003222","display_name":"Roland Siegwart","orcid":"https://orcid.org/0000-0002-2760-7983"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Roland Siegwart","raw_affiliation_strings":["Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059792297","display_name":"Juan Nieto","orcid":"https://orcid.org/0000-0003-4808-0831"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Juan Nieto","raw_affiliation_strings":["Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autonomous Systems Lab, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.7908,"has_fulltext":false,"cited_by_count":102,"citation_normalized_percentile":{"value":0.99486548,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"2016","issue":null,"first_page":"2607","last_page":"2612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"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":0.9997000098228455,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9988999962806702,"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":0.8608675599098206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7875051498413086},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6376246213912964},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6270062327384949},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5882653594017029},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5688644647598267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5638618469238281},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5583403706550598},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5499406456947327},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5005903244018555},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4852452278137207},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44884926080703735},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4327573776245117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42082875967025757},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.11495178937911987},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10940796136856079},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10482534766197205}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8608675599098206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875051498413086},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6376246213912964},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6270062327384949},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5882653594017029},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5688644647598267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5638618469238281},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5583403706550598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5499406456947327},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5005903244018555},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4852452278137207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44884926080703735},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4327573776245117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42082875967025757},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.11495178937911987},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10940796136856079},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10482534766197205},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2016.7795975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2016.7795975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"mag:2752141962","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702241815624141","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1165382972","https://openalex.org/W1606347560","https://openalex.org/W1665214252","https://openalex.org/W1829255258","https://openalex.org/W1896053897","https://openalex.org/W1980985548","https://openalex.org/W2004641798","https://openalex.org/W2031638733","https://openalex.org/W2037629065","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2101415982","https://openalex.org/W2150823086","https://openalex.org/W2154458843","https://openalex.org/W2163605009","https://openalex.org/W2415953079","https://openalex.org/W2736205458","https://openalex.org/W6600284362","https://openalex.org/W6627641123","https://openalex.org/W6636358008","https://openalex.org/W6637242042","https://openalex.org/W6651503529","https://openalex.org/W6674330103","https://openalex.org/W6674955169","https://openalex.org/W6684191040","https://openalex.org/W6715959869","https://openalex.org/W7052487566"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W3122828758","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2330964916"],"abstract_inverted_index":{"In":[0,61,87,110],"the":[1,17,28,39,67,77,114,137,141,147],"context":[2],"of":[3,21,30,49,69,79,116,170],"future":[4],"urban":[5,25,59],"automated":[6],"driving":[7],"many":[8],"important":[9],"problems":[10],"remain":[11],"unsolved.":[12],"A":[13],"critical":[14],"one":[15],"is":[16],"analysis":[18,29],"and":[19,46,76,118],"prediction":[20,149],"pedestrian":[22,84],"movements":[23,48],"around":[24],"roads.":[26],"Especially":[27],"non-critical":[31],"situations":[32],"has":[33],"not":[34],"received":[35],"much":[36],"attention":[37],"in":[38,58,161],"past.":[40],"This":[41],"paper":[42],"focuses":[43],"on":[44,104],"analyzing":[45],"predicting":[47],"pedestrians":[50],"approaching":[51],"crosswalks,":[52],"a":[53,70],"very":[54],"crucial":[55],"pedestrian-vehicle":[56],"interaction":[57],"scenarios.":[60],"our":[62,93,128,175],"previous":[63,94,176],"work,":[64],"we":[65,90,112,122],"analyzed":[66],"performance":[68],"data-driven":[71],"Support":[72,177],"Vector":[73,178],"Machine-based":[74,179],"architecture,":[75],"relevance":[78],"specific":[80],"features":[81],"to":[82,98,136,174],"infer":[83],"crossing":[85],"intentions.":[86],"this":[88],"paper,":[89],"will":[91,123],"use":[92],"results":[95,164],"as":[96],"baseline":[97],"compare":[99],"against":[100],"an":[101,144,166],"architecture":[102],"based":[103,134],"neural":[105],"networks":[106],"for":[107,146],"time-series":[108],"classification.":[109],"particular":[111],"analyze":[113],"effectiveness":[115],"dense":[117],"Long-Short-Term-Memory":[119],"networks.":[120],"Furthermore,":[121],"be":[124],"looking":[125],"into":[126],"enhancing":[127],"feature":[129],"vectors":[130],"by":[131],"adding":[132],"LiDAR":[133],"images":[135],"classification":[138],"process.":[139],"Additionally":[140],"evaluation":[142],"provides":[143],"estimate":[145],"temporal":[148],"horizon.":[150],"The":[151],"approaches":[152],"presented":[153],"are":[154],"validated":[155],"with":[156,172],"real":[157],"world":[158],"trajectories":[159],"recorded":[160],"Germany.":[162],"Our":[163],"show":[165],"average":[167],"accuracy":[168],"improvement":[169],"10\u201320%":[171],"respect":[173],"approach.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":16},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}