{"id":"https://openalex.org/W2891385160","doi":"https://doi.org/10.1109/itsc.2018.8569453","title":"Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning","display_name":"Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2891385160","doi":"https://doi.org/10.1109/itsc.2018.8569453","mag":"2891385160"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2018.8569453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","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/A5087667477","display_name":"Liting Sun","orcid":"https://orcid.org/0000-0002-1248-2137"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liting Sun","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101770873","display_name":"Wei Zhan","orcid":"https://orcid.org/0000-0002-1474-1200"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Zhan","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064077634","display_name":"Masayoshi Tomizuka","orcid":"https://orcid.org/0000-0003-0206-6639"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masayoshi Tomizuka","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087667477"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":9.2678,"has_fulltext":false,"cited_by_count":139,"citation_normalized_percentile":{"value":0.98194296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2111","last_page":"2117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9993000030517578,"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":0.9993000030517578,"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/T10524","display_name":"Traffic control and management","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9735000133514404,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.809860348701477},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7179116010665894},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7004701495170593},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6041756272315979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5344530344009399},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5049455761909485},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5004956722259521},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4493301212787628},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1541149914264679}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.809860348701477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7179116010665894},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7004701495170593},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6041756272315979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5344530344009399},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5049455761909485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5004956722259521},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4493301212787628},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1541149914264679},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2018.8569453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1533707276","https://openalex.org/W1579853615","https://openalex.org/W1801976851","https://openalex.org/W1970916399","https://openalex.org/W2017989066","https://openalex.org/W2021472139","https://openalex.org/W2061562262","https://openalex.org/W2073241381","https://openalex.org/W2095932903","https://openalex.org/W2098774185","https://openalex.org/W2125838338","https://openalex.org/W2152374007","https://openalex.org/W2165216595","https://openalex.org/W2227909145","https://openalex.org/W2281287867","https://openalex.org/W2343781317","https://openalex.org/W2411577903","https://openalex.org/W2539337444","https://openalex.org/W2609292110","https://openalex.org/W2739770424","https://openalex.org/W2739974901","https://openalex.org/W2740526166","https://openalex.org/W2741087535","https://openalex.org/W2789714787","https://openalex.org/W2890157627","https://openalex.org/W2950465931","https://openalex.org/W2963489164","https://openalex.org/W2963787234","https://openalex.org/W3104790740","https://openalex.org/W6674884181","https://openalex.org/W6753730925","https://openalex.org/W6754889522"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W3131574667","https://openalex.org/W2009776842"],"abstract_inverted_index":{"Autonomous":[0],"vehicles":[1,25,71],"(AVs)":[2],"are":[3],"on":[4,61,66,88,113],"the":[5,21,36,48,55,98,115,122,134,144,154,165,172,184],"road.":[6],"To":[7,76],"safely":[8],"and":[9,26,108],"efficiently":[10],"interact":[11,73],"with":[12,74],"other":[13,70],"road":[14],"participants,":[15],"AVs":[16],"have":[17],"to":[18,34,142],"accurately":[19,169],"predict":[20,170],"behavior":[22],"of":[23,54,69,102,121,130],"surrounding":[24],"plan":[27],"accordingly.":[28],"Such":[29,41],"prediction":[30,42,85],"should":[31,43],"be":[32,45],"probabilistic,":[33],"address":[35],"uncertainties":[37],"in":[38],"human":[39,103,148],"behavior.":[40],"also":[44,65],"interactive,":[46],"since":[47],"distribution":[49,116],"over":[50,117],"all":[51,118],"possible":[52],"trajectories":[53,120],"predicted":[56,123],"vehicle":[57,124],"depends":[58],"not":[59],"only":[60],"historical":[62],"information,":[63],"but":[64],"future":[67,119],"plans":[68],"that":[72,164],"it.":[75],"achieve":[77],"such":[78,176],"interaction-aware":[79],"predictions,":[80],"we":[81,95,138],"propose":[82],"a":[83,128],"probabilistic":[84],"approach":[86,167],"based":[87],"hierarchical":[89,99],"inverse":[90],"reinforcement":[91],"learning":[92],"(IRL).":[93],"First,":[94],"explicitly":[96],"consider":[97],"trajectory-generation":[100],"process":[101],"drivers":[104],"involving":[105],"both":[106,171],"discrete":[107,135,173],"continuous":[109,185],"driving":[110,156,174],"decisions.":[111,136],"Based":[112],"this,":[114],"is":[125,158],"formulated":[126],"as":[127,177,181,183],"mixture":[129],"distributions":[131,145],"partitioned":[132],"by":[133],"Then":[137],"apply":[139],"IRL":[140],"hierarchically":[141],"learn":[143],"from":[146],"real":[147],"demonstrations.":[149],"A":[150],"case":[151],"study":[152],"for":[153],"ramp-merging":[155],"scenario":[157],"provided.":[159],"The":[160],"quantitative":[161],"results":[162],"show":[163],"proposed":[166],"can":[168],"decisions":[175],"yield":[178],"or":[179],"pass":[180],"well":[182],"trajectories.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}