{"id":"https://openalex.org/W3082841044","doi":"https://doi.org/10.3390/s20174887","title":"A Hybrid Approach for Turning Intention Prediction Based on Time Series Forecasting and Deep Learning","display_name":"A Hybrid Approach for Turning Intention Prediction Based on Time Series Forecasting and Deep Learning","publication_year":2020,"publication_date":"2020-08-28","ids":{"openalex":"https://openalex.org/W3082841044","doi":"https://doi.org/10.3390/s20174887","mag":"3082841044","pmid":"https://pubmed.ncbi.nlm.nih.gov/32872356"},"language":"en","primary_location":{"id":"doi:10.3390/s20174887","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174887","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4887/pdf?version=1599014160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/17/4887/pdf?version=1599014160","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045034851","display_name":"Hailun Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailun Zhang","raw_affiliation_strings":["School of Automobile, Chang\u2019an University, Xi\u2019an 710064, China","School of Automobile, Chang'an University, Xi'an 710064, China"],"raw_orcid":"https://orcid.org/0000-0003-2161-4741","affiliations":[{"raw_affiliation_string":"School of Automobile, Chang\u2019an University, Xi\u2019an 710064, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"School of Automobile, Chang'an University, Xi'an 710064, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047611545","display_name":"Rui Fu","orcid":"https://orcid.org/0009-0007-3873-2898"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]},{"id":"https://openalex.org/I4210127216","display_name":"Ministry of Transport","ror":"https://ror.org/031wq1t38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Fu","raw_affiliation_strings":["Key Lab of Vehicle Transportation Safety Technology, Ministry of Transport, Chang\u2019an University, Xi\u2019an 710064, China","School of Automobile, Chang\u2019an University, Xi\u2019an 710064, China","School of Automobile, Chang'an University, Xi'an 710064, China","Key Lab of Vehicle Transportation Safety Technology, Ministry of Transport, Chang'an University, Xi'an 710064, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab of Vehicle Transportation Safety Technology, Ministry of Transport, Chang\u2019an University, Xi\u2019an 710064, China","institution_ids":["https://openalex.org/I25355098","https://openalex.org/I4210127216"]},{"raw_affiliation_string":"School of Automobile, Chang\u2019an University, Xi\u2019an 710064, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"School of Automobile, Chang'an University, Xi'an 710064, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"Key Lab of Vehicle Transportation Safety Technology, Ministry of Transport, Chang'an University, Xi'an 710064, China","institution_ids":["https://openalex.org/I25355098","https://openalex.org/I4210127216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047611545"],"corresponding_institution_ids":["https://openalex.org/I25355098","https://openalex.org/I4210127216"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.5218,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.81182592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"20","issue":"17","first_page":"4887","last_page":"4887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9988999962806702,"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":0.9988999962806702,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9970999956130981,"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/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8117064833641052},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.7012673616409302},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.660001814365387},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.6254814267158508},{"id":"https://openalex.org/keywords/heading","display_name":"Heading (navigation)","score":0.5729238986968994},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5470283627510071},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5172146558761597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5147345066070557},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5086401700973511},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.494505375623703},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.49013790488243103},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4819033443927765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4638405442237854},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45838943123817444},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.43975722789764404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3009644150733948},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.25421324372291565},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11095577478408813},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.11041229963302612}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8117064833641052},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.7012673616409302},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.660001814365387},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.6254814267158508},{"id":"https://openalex.org/C2776937971","wikidata":"https://www.wikidata.org/wiki/Q4384217","display_name":"Heading (navigation)","level":2,"score":0.5729238986968994},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5470283627510071},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5172146558761597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5147345066070557},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5086401700973511},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.494505375623703},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.49013790488243103},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4819033443927765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4638405442237854},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45838943123817444},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.43975722789764404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3009644150733948},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25421324372291565},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11095577478408813},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.11041229963302612},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20174887","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174887","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4887/pdf?version=1599014160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32872356","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32872356","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f9eb8cc412784472a5bf7e6bae76c5fd","is_oa":true,"landing_page_url":"https://doaj.org/article/f9eb8cc412784472a5bf7e6bae76c5fd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 17, p 4887 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/17/4887/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20174887","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 20; Issue 17; Pages: 4887","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7506877","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7506877","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20174887","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174887","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4887/pdf?version=1599014160","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2444590990","display_name":null,"funder_award_id":"CHD 300102220202","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2708501254","display_name":null,"funder_award_id":"300102220202","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4625672317","display_name":null,"funder_award_id":"51908054","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5868862716","display_name":null,"funder_award_id":"2018YFB1600500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6245479638","display_name":null,"funder_award_id":"300102220202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7134538149","display_name":null,"funder_award_id":"51908054","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7579424075","display_name":null,"funder_award_id":"2018YFB1600500","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8551535818","display_name":null,"funder_award_id":"51908054","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3082841044.pdf","grobid_xml":"https://content.openalex.org/works/W3082841044.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W799832950","https://openalex.org/W1789187189","https://openalex.org/W1982791281","https://openalex.org/W2006303452","https://openalex.org/W2011369927","https://openalex.org/W2012849708","https://openalex.org/W2037985840","https://openalex.org/W2060797806","https://openalex.org/W2064675550","https://openalex.org/W2084246939","https://openalex.org/W2128060716","https://openalex.org/W2148825261","https://openalex.org/W2185366893","https://openalex.org/W2341256225","https://openalex.org/W2442734498","https://openalex.org/W2503062631","https://openalex.org/W2527707434","https://openalex.org/W2531361673","https://openalex.org/W2542945130","https://openalex.org/W2579911499","https://openalex.org/W2582443945","https://openalex.org/W2596110958","https://openalex.org/W2739303852","https://openalex.org/W2741066535","https://openalex.org/W2741087535","https://openalex.org/W2782414634","https://openalex.org/W2784715585","https://openalex.org/W2792239816","https://openalex.org/W2803184913","https://openalex.org/W2805499321","https://openalex.org/W2806373172","https://openalex.org/W2809653114","https://openalex.org/W2883602772","https://openalex.org/W2892035503","https://openalex.org/W2897599001","https://openalex.org/W2907176255","https://openalex.org/W2907511648","https://openalex.org/W2914767245","https://openalex.org/W2917883546","https://openalex.org/W2932653301","https://openalex.org/W2945374197","https://openalex.org/W2946476763","https://openalex.org/W2947444283","https://openalex.org/W2949613690","https://openalex.org/W2954045886","https://openalex.org/W2955787963","https://openalex.org/W2961359668","https://openalex.org/W2963692464","https://openalex.org/W2964020895","https://openalex.org/W2964118901","https://openalex.org/W2964145578","https://openalex.org/W2964514043","https://openalex.org/W2967118105","https://openalex.org/W2969239003","https://openalex.org/W2976036462","https://openalex.org/W2999094186","https://openalex.org/W3005217278","https://openalex.org/W3104946437","https://openalex.org/W3105115779","https://openalex.org/W6766469832"],"related_works":["https://openalex.org/W3190289737","https://openalex.org/W3115491726","https://openalex.org/W2073847544","https://openalex.org/W2567143433","https://openalex.org/W2620501840","https://openalex.org/W2085237988","https://openalex.org/W3032070712","https://openalex.org/W2518538438","https://openalex.org/W4313123484","https://openalex.org/W4401065000"],"abstract_inverted_index":{"At":[0],"an":[1],"intersection":[2],"with":[3],"complex":[4],"traffic":[5],"flow,":[6],"the":[7,11,27,37,49,63,95,104,109,121,127,138,143,149,153,164,173,178,187,193,204,221],"early":[8],"detection":[9,190],"of":[10,13,52,103,120,163,177,186],"intention":[12,65],"drivers":[14,44],"in":[15,29],"surrounding":[16],"vehicles":[17,54],"can":[18,55],"enable":[19],"advanced":[20],"driver":[21,28],"assistance":[22],"systems":[23],"(ADAS)":[24],"to":[25,35,136],"warn":[26],"advance":[30],"or":[31],"prompt":[32],"its":[33],"subsystems":[34],"assess":[36],"risk":[38],"and":[39,90,101,158,210,215],"intervene":[40],"early.":[41],"Although":[42],"different":[43],"show":[45,191],"various":[46],"driving":[47,175],"characteristics,":[48],"kinematic":[50],"parameters":[51],"human-driven":[53],"be":[56],"used":[57,135],"as":[58,146,148],"a":[59,67,75,118,201],"predictor":[60],"for":[61,79],"predicting":[62],"driver's":[64],"within":[66],"short":[68],"time.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"propose":[74],"new":[76],"hybrid":[77,195],"approach":[78,196],"vehicle":[80,105],"behavior":[81,141,189],"recognition":[82,206],"at":[83,169,212],"intersections":[84,171],"based":[85],"on":[86],"time":[87],"series":[88],"prediction":[89],"deep":[91],"learning":[92],"networks.":[93],"First,":[94],"lateral":[96,154,156],"position,":[97,99],"longitudinal":[98],"speed,":[100],"acceleration":[102],"are":[106,208],"predicted":[107,144],"using":[108,142,172],"online":[110],"autoregressive":[111],"integrated":[112],"moving":[113],"average":[114,205],"(ARIMA)":[115],"algorithm.":[116],"Next,":[117],"variant":[119],"long":[122,129],"short-term":[123,130],"memory":[124,131],"network,":[125,133],"called":[126],"bidirectional":[128],"(Bi-LSTM)":[132],"is":[134,167],"detect":[137],"vehicle's":[139],"turning":[140,188,222],"parameters,":[145,151],"well":[147],"derived":[150],"i.e.,":[152],"velocity,":[155],"acceleration,":[157],"heading":[159],"angle.":[160],"The":[161,184],"validity":[162],"proposed":[165,194],"method":[166],"verified":[168],"real":[170],"public":[174],"data":[176],"next":[179],"generation":[180],"simulation":[181],"(NGSIM)":[182],"project.":[183],"results":[185],"that":[192],"exhibits":[197],"significant":[198],"improvement":[199],"over":[200],"conventional":[202],"algorithm;":[203],"rates":[207],"94.2%":[209],"93.5%":[211],"2":[213],"s":[214],"1":[216],"s,":[217],"respectively,":[218],"before":[219],"initiating":[220],"maneuver.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-26T07:53:14.480251","created_date":"2025-10-10T00:00:00"}