{"id":"https://openalex.org/W3040858909","doi":"https://doi.org/10.1109/iros45743.2020.9340636","title":"Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning","display_name":"Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3040858909","doi":"https://doi.org/10.1109/iros45743.2020.9340636","mag":"3040858909"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9340636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9340636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.05798","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054554868","display_name":"Sascha Rosbach","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Sascha Rosbach","raw_affiliation_strings":["Volkswagen AG,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Volkswagen AG,Wolfsburg,Germany,38440","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358708","display_name":"Xing Li","orcid":"https://orcid.org/0000-0003-3793-1581"},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xing Li","raw_affiliation_strings":["Volkswagen AG,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Volkswagen AG,Wolfsburg,Germany,38440","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021752598","display_name":"Simon Grosjohann","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Simon Grosjohann","raw_affiliation_strings":["Volkswagen AG,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Volkswagen AG,Wolfsburg,Germany,38440","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000788588","display_name":"Silviu Homoceanu","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Silviu Homoceanu","raw_affiliation_strings":["Volkswagen AG,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Volkswagen AG,Wolfsburg,Germany,38440","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056098625","display_name":"Stefan Roth","orcid":"https://orcid.org/0000-0001-9002-9832"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Roth","raw_affiliation_strings":["Technische Universit\u00e4t Darmstadt,Visual Inference Lab,Department of Computer Science,64289,Germany,Darmstadt"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Darmstadt,Visual Inference Lab,Department of Computer Science,64289,Germany,Darmstadt","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054554868"],"corresponding_institution_ids":["https://openalex.org/I1319473763"],"apc_list":null,"apc_paid":null,"fwci":0.6097,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.69515781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5187","last_page":"5193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983999729156494,"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":0.9983999729156494,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8645117282867432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7513061761856079},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6360316872596741},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6303525567054749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5563884973526001},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5438944697380066},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4665994644165039},{"id":"https://openalex.org/keywords/time-horizon","display_name":"Time horizon","score":0.4348723590373993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3735988140106201},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2165757119655609},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.1331508755683899},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11285638809204102}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8645117282867432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513061761856079},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6360316872596741},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6303525567054749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5563884973526001},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5438944697380066},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4665994644165039},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.4348723590373993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3735988140106201},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2165757119655609},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.1331508755683899},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11285638809204102},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros45743.2020.9340636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9340636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.05798","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.05798","pdf_url":"https://arxiv.org/pdf/2007.05798","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.05798","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.05798","pdf_url":"https://arxiv.org/pdf/2007.05798","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1925816294","https://openalex.org/W1983304737","https://openalex.org/W2061562262","https://openalex.org/W2098774185","https://openalex.org/W2109910161","https://openalex.org/W2133564696","https://openalex.org/W2153284231","https://openalex.org/W2155098712","https://openalex.org/W2172806452","https://openalex.org/W2181849516","https://openalex.org/W2344349469","https://openalex.org/W2530849036","https://openalex.org/W2565410644","https://openalex.org/W2601322194","https://openalex.org/W2790798766","https://openalex.org/W2800753541","https://openalex.org/W2804078698","https://openalex.org/W2809461852","https://openalex.org/W2942735643","https://openalex.org/W2950893734","https://openalex.org/W2957408986","https://openalex.org/W2962919668","https://openalex.org/W2963094133","https://openalex.org/W2963811535","https://openalex.org/W2964308564","https://openalex.org/W2992382489","https://openalex.org/W3005581722","https://openalex.org/W3101805180","https://openalex.org/W3104181348","https://openalex.org/W4294557331","https://openalex.org/W4301501993","https://openalex.org/W6640290305","https://openalex.org/W6674884181","https://openalex.org/W6679434410","https://openalex.org/W6684983439","https://openalex.org/W6685962732","https://openalex.org/W6704216233","https://openalex.org/W6735944222","https://openalex.org/W6752356361","https://openalex.org/W6752378368"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W1941703695","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W4248382324","https://openalex.org/W2024136090","https://openalex.org/W3131574667","https://openalex.org/W2586732548"],"abstract_inverted_index":{"General-purpose":[0],"trajectory":[1,76],"planning":[2,77,110,226],"algorithms":[3,78],"for":[4,176],"automated":[5],"driving":[6,73,88,159,188],"utilize":[7],"complex":[8,186],"reward":[9,29,64,127],"functions":[10,65],"to":[11,60,81,94,146,170,203],"perform":[12],"a":[13,27,32,40,69,83,99,136,142,148,157,166],"combined":[14],"optimization":[15],"of":[16,26,43,68,71,86,98,179],"strategic,":[17],"behavioral,":[18],"and":[19,24,35,174],"kinematic":[20],"features.":[21],"The":[22],"specification":[23],"tuning":[25],"single":[28],"function":[30],"is":[31],"tedious":[33],"task":[34],"does":[36],"not":[37],"generalize":[38],"over":[39,129,223],"large":[41],"set":[42,70],"traffic":[44],"situations.":[45],"Deep":[46],"learning":[47,55],"approaches":[48],"based":[49],"on":[50,114,154,185,205],"path":[51],"integral":[52],"inverse":[53],"reinforcement":[54],"have":[56],"been":[57],"successfully":[58],"applied":[59],"predict":[61],"local":[62],"situation-dependent":[63],"using":[66],"features":[67],"sampled":[72],"policies.":[74],"Sample-based":[75],"are":[79,122],"able":[80],"approximate":[82],"spatio-temporal":[84],"subspace":[85],"feasible":[87],"policies":[89,207],"that":[90,140,197],"can":[91],"be":[92],"used":[93],"encode":[95],"the":[96,102,125,209,213],"context":[97,116,150,172],"situation.":[100],"However,":[101],"interaction":[103,219],"with":[104,124,156,220],"dynamic":[105],"objects":[106],"requires":[107],"an":[108,130,224],"extended":[109,131,225],"horizon,":[111],"which":[112],"depends":[113],"sequential":[115,126],"modeling.":[117],"In":[118],"this":[119],"work,":[120],"we":[121,164],"concerned":[123],"prediction":[128],"time":[132],"horizon.":[133,227],"We":[134,181],"present":[135],"neural":[137],"network":[138],"architecture":[139],"uses":[141],"policy":[143,199],"attention":[144,168,200,215],"mechanism":[145,169,201,216],"generate":[147],"low-dimensional":[149],"vector":[151],"by":[152],"concentrating":[153],"trajectories":[155],"human-like":[158],"style.":[160],"Apart":[161],"from":[162],"this,":[163],"propose":[165],"temporal":[167,214],"identify":[171],"switches":[173],"allow":[175],"stable":[177],"adaptation":[178],"rewards.":[180],"evaluate":[182],"our":[183,198],"results":[184],"simulated":[187],"situations,":[189],"including":[190],"other":[191,221],"moving":[192],"vehicles.":[193],"Our":[194],"evaluation":[195],"shows":[196],"learns":[202,217],"focus":[204],"collision-free":[206],"in":[208],"configuration":[210],"space.":[211],"Furthermore,":[212],"persistent":[218],"vehicles":[222]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-07-16T00:00:00"}
