{"id":"https://openalex.org/W3004922758","doi":"https://doi.org/10.1145/3372422.3372428","title":"A Method of Pedestrian Trajectory Prediction Based on LSTM","display_name":"A Method of Pedestrian Trajectory Prediction Based on LSTM","publication_year":2019,"publication_date":"2019-11-23","ids":{"openalex":"https://openalex.org/W3004922758","doi":"https://doi.org/10.1145/3372422.3372428","mag":"3004922758"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372422.3372428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5101765430","display_name":"Xuefeng Jiang","orcid":"https://orcid.org/0000-0002-6740-6836"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Jiang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636010","display_name":"Wei Lin","orcid":"https://orcid.org/0000-0001-8425-956X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Lin","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102883539","display_name":"Junrui Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junrui Liu","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.412,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.602347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":79,"max":81},"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"84"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.999,"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":0.999,"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":0.9968,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9955,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.57750326},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5682876}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.862833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7777809},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.71839046},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.69160414},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6175347},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5915214},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.57750326},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5682876},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5481558},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49897194},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47032416},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4338606},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0850068},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372422.3372428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":17,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W179875071","https://openalex.org/W1967777429","https://openalex.org/W1970206276","https://openalex.org/W2064675550","https://openalex.org/W2102113734","https://openalex.org/W2107775979","https://openalex.org/W2134944993","https://openalex.org/W2136848157","https://openalex.org/W2167052694","https://openalex.org/W2171928131","https://openalex.org/W2424778531","https://openalex.org/W2518708963","https://openalex.org/W2532516272","https://openalex.org/W2593239008","https://openalex.org/W2963403868","https://openalex.org/W4234552385"],"related_works":["https://openalex.org/W49697837","https://openalex.org/W4225394202","https://openalex.org/W4205958986","https://openalex.org/W3122828758","https://openalex.org/W3008584592","https://openalex.org/W2586575957","https://openalex.org/W2512789322","https://openalex.org/W2392100589","https://openalex.org/W2197846993","https://openalex.org/W2101960027"],"abstract_inverted_index":{"In":[0,87],"the":[1,30,34,39,51,64,77,139,147],"public":[2],"scene,":[3],"different":[4,8],"pedestrian":[5],"walks":[6],"on":[7,50,83,143],"paths":[9],"to":[10,28,46,75,120],"avoid":[11,47],"colliding":[12],"with":[13],"obstacles":[14],"or":[15],"others.":[16],"Any":[17],"small":[18],"vehicle":[19],"navigation":[20],"in":[21,73,98],"such":[22],"a":[23,55,106,128,154],"scenario":[24],"should":[25],"be":[26,61],"able":[27],"anticipate":[29],"approximate":[31],"position":[32],"of":[33,57,66,80],"people":[35],"around":[36],"it":[37,152],"at":[38],"next":[40],"moment,":[41],"and":[42,69,112,146],"adjust":[43],"its":[44],"path":[45],"collisions":[48],"based":[49,82],"predicted":[52],"results.":[53],"Such":[54],"problem":[56],"trajectory":[58,79,131],"prediction":[59,100],"can":[60,126],"regarded":[62],"as":[63],"task":[65],"sequence":[67,99],"generation,":[68],"we":[70],"are":[71],"interested":[72],"how":[74],"predict":[76,127],"future":[78,130],"pedestrians":[81],"their":[84],"past":[85,135],"trajectory.":[86,136],"recent":[88],"years,":[89],"Recurrent":[90],"Neural":[91],"Network":[92],"(RNN)":[93],"model":[94,107,125,140],"has":[95,153],"been":[96],"successful":[97],"tasks.":[101],"So,":[102],"this":[103,122],"paper":[104],"proposes":[105],"combining":[108],"an":[109],"attention":[110],"mechanism":[111],"Long":[113],"Short-Term":[114],"Memory":[115],"(LSTM)":[116],"artificial":[117],"neural":[118],"networks,":[119],"solve":[121],"question.":[123],"This":[124],"pedestrian's":[129],"by":[132],"learning":[133],"his":[134],"Experiments":[137],"shows":[138],"work":[141],"well":[142],"multiple":[144],"datasets,":[145],"test":[148],"results":[149],"show":[150],"that":[151],"very":[155],"good":[156],"effect.":[157]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3004922758","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2024-12-09T05:16:39.883473","created_date":"2020-02-14"}