{"id":"https://openalex.org/W2734463498","doi":"https://doi.org/10.23919/acc.2017.7962970","title":"Similarity-based vehicle-motion prediction","display_name":"Similarity-based vehicle-motion prediction","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2734463498","doi":"https://doi.org/10.23919/acc.2017.7962970","mag":"2734463498"},"language":"en","primary_location":{"id":"doi:10.23919/acc.2017.7962970","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7962970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","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/A5000307667","display_name":"Kazuhide Okamoto","orcid":"https://orcid.org/0000-0003-4222-8356"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kazuhide Okamoto","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090118616","display_name":"Karl Berntorp","orcid":"https://orcid.org/0000-0002-6809-6657"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karl Berntorp","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004144091","display_name":"Stefano Di Cairano","orcid":"https://orcid.org/0000-0002-2363-2807"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stefano Di Cairano","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000307667"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.755,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86548597,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"303","last_page":"308"},"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":0.9984999895095825,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.6922879815101624},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.6633403897285461},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6488634347915649},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6444482207298279},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6314820051193237},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5779423117637634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138688087463379},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.470132440328598},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4627532958984375},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.43190357089042664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4162130653858185},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40966954827308655},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19633686542510986},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1732076108455658}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6922879815101624},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.6633403897285461},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6488634347915649},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6444482207298279},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6314820051193237},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5779423117637634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138688087463379},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.470132440328598},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4627532958984375},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.43190357089042664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4162130653858185},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40966954827308655},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19633686542510986},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1732076108455658},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc.2017.7962970","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7962970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W95577512","https://openalex.org/W192453454","https://openalex.org/W1673310716","https://openalex.org/W1968701380","https://openalex.org/W2014414177","https://openalex.org/W2069544315","https://openalex.org/W2097545165","https://openalex.org/W2110707662","https://openalex.org/W2128160875","https://openalex.org/W2152206601","https://openalex.org/W2166343746","https://openalex.org/W2343568200","https://openalex.org/W2402106645","https://openalex.org/W2491273080","https://openalex.org/W2911964244","https://openalex.org/W6607858583","https://openalex.org/W6637131181"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340"],"abstract_inverted_index":{"Motion-prediction":[0],"algorithms":[1],"for":[2,101],"vehicles":[3,95],"often":[4],"employ":[5],"historical":[6],"behavior":[7,24,73],"of":[8,16,25,55,69,74,83,92,136,143],"a":[9,49,70,75,102],"vehicle,":[10,71],"rely":[11],"on":[12],"the":[13,17,22,26,29,53,67,72,90,99,117,134,141,144],"Markov":[14,30],"property":[15,31],"underlying":[18],"system,":[19],"and":[20,38,63,132],"predict":[21],"future":[23],"vehicle.":[27],"However,":[28],"alone":[32],"may":[33],"lead":[34],"to":[35,81,128],"conservative":[36],"predictions":[37],"heavy":[39],"computational":[40],"burden.":[41],"To":[42],"overcome":[43],"these":[44],"drawbacks,":[45],"this":[46,126],"paper":[47,120],"develops":[48],"method":[50],"that":[51,82,88,111,124],"uses":[52],"notion":[54],"similarity":[56],"among":[57],"vehicle":[58,77],"trajectories.":[59],"As":[60],"traffic":[61],"rules":[62],"driver":[64],"intentions":[65],"restrict":[66],"motions":[68],"road":[76],"is":[78,109],"typically":[79],"similar":[80,97,115],"other":[84],"vehicles.":[85],"We":[86],"hypothesize":[87],"if":[89],"motion":[91],"any":[93],"two":[94],"was":[96],"in":[98,116],"past":[100],"sufficiently":[103],"long":[104],"time":[105],"span,":[106],"then":[107],"it":[108,112,139],"likely":[110],"will":[113],"be":[114],"future.":[118],"This":[119],"introduces":[121],"an":[122],"algorithm":[123],"exploits":[125],"hypothesis":[127],"develop":[129],"prediction":[130],"methods,":[131],"from":[133],"results":[135],"numerical":[137],"simulations,":[138],"verifies":[140],"effectiveness":[142],"algorithm.":[145]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}