{"id":"https://openalex.org/W4304814768","doi":"https://doi.org/10.1109/acit54803.2022.9912747","title":"Exploiting Stage Information for Prediction of Switching Times of Traffic Actuated Signals Using Machine Learning","display_name":"Exploiting Stage Information for Prediction of Switching Times of Traffic Actuated Signals Using Machine Learning","publication_year":2022,"publication_date":"2022-09-26","ids":{"openalex":"https://openalex.org/W4304814768","doi":"https://doi.org/10.1109/acit54803.2022.9912747"},"language":"en","primary_location":{"id":"doi:10.1109/acit54803.2022.9912747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit54803.2022.9912747","pdf_url":null,"source":{"id":"https://openalex.org/S4363608254","display_name":"2022 12th International Conference on Advanced Computer Information Technologies (ACIT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 12th International Conference on Advanced Computer Information Technologies (ACIT)","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/A5085580015","display_name":"Lena Elisa Scheegans","orcid":null},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Lena Elisa Scheegans","raw_affiliation_strings":["University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany"],"affiliations":[{"raw_affiliation_string":"University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","institution_ids":["https://openalex.org/I106157433"]},{"raw_affiliation_string":"Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009879718","display_name":"Kevin Heckmann","orcid":"https://orcid.org/0000-0002-2798-2599"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kevin Heckmann","raw_affiliation_strings":["University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany"],"affiliations":[{"raw_affiliation_string":"University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","institution_ids":["https://openalex.org/I106157433"]},{"raw_affiliation_string":"Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029316549","display_name":"Robert Hoyer","orcid":"https://orcid.org/0009-0002-8807-8250"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Robert Hoyer","raw_affiliation_strings":["University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany"],"affiliations":[{"raw_affiliation_string":"University of Kassel,Department of Traffic Engineering and Transport Logistics,Kassel,Germany","institution_ids":["https://openalex.org/I106157433"]},{"raw_affiliation_string":"Department of Traffic Engineering and Transport Logistics, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085580015"],"corresponding_institution_ids":["https://openalex.org/I106157433"],"apc_list":null,"apc_paid":null,"fwci":1.0119,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72626841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"544","last_page":"548"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"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/T10524","display_name":"Traffic control and management","score":0.9980999827384949,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6648212671279907},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5688632726669312},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.550589919090271},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5439403653144836},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5374778509140015},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.47843435406684875},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.45625078678131104},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.41168013215065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3906106948852539},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.2772694230079651},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22708597779273987},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2244029939174652}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6648212671279907},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5688632726669312},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.550589919090271},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5439403653144836},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5374778509140015},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.47843435406684875},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.45625078678131104},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.41168013215065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3906106948852539},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.2772694230079651},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22708597779273987},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2244029939174652},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit54803.2022.9912747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit54803.2022.9912747","pdf_url":null,"source":{"id":"https://openalex.org/S4363608254","display_name":"2022 12th International Conference on Advanced Computer Information Technologies (ACIT)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 12th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6700000166893005}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W26849536","https://openalex.org/W154276503","https://openalex.org/W2077842246","https://openalex.org/W2129180599","https://openalex.org/W2152918251","https://openalex.org/W2157525649","https://openalex.org/W2169568254","https://openalex.org/W2295598076","https://openalex.org/W2749706572","https://openalex.org/W2757129036","https://openalex.org/W3000566345","https://openalex.org/W3116366664","https://openalex.org/W3157739000","https://openalex.org/W3212240640","https://openalex.org/W4205634339","https://openalex.org/W4321455335","https://openalex.org/W4368250100","https://openalex.org/W6606309025","https://openalex.org/W6743642417","https://openalex.org/W6744258730","https://openalex.org/W6794408689","https://openalex.org/W6849903224","https://openalex.org/W6852397530"],"related_works":["https://openalex.org/W2393348402","https://openalex.org/W2242021741","https://openalex.org/W2377015873","https://openalex.org/W2605253768","https://openalex.org/W3044060590","https://openalex.org/W22276206","https://openalex.org/W2392201083","https://openalex.org/W1607802202","https://openalex.org/W2565438091","https://openalex.org/W2396489752"],"abstract_inverted_index":{"Traffic":[0,73],"jams":[1],"and":[2,39,131,140,174],"stops":[3],"in":[4,41],"front":[5,42],"of":[6,14,32,43,58,66,79,103,118,162,171,177],"(signalized)":[7],"intersections":[8],"are":[9,147],"causing":[10],"a":[11,76,137,141],"significant":[12],"amount":[13],"road":[15],"traffic":[16,44,59,67,172,175,179],"emissions.":[17],"Reliable":[18],"signal":[19,80,94,127],"timing":[20],"estimation":[21,117],"integrated":[22],"into":[23,86],"Green":[24],"Light":[25],"Optimal":[26],"Speed":[27],"Advisory":[28],"systems":[29],"is":[30],"one":[31,90],"the":[33,63,93,101,104,116,119,153,160,163,165,169,178],"keys":[34],"to":[35,61,88],"minimizing":[36],"unnecessary":[37],"braking":[38],"accelerating":[40],"lights.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,134],"present":[50],"experiments":[51],"based":[52,124],"on":[53,99,126,168],"recorded":[54],"real-world":[55],"process":[56],"data":[57],"signals":[60,69],"predict":[62],"switching":[64,120],"times":[65,121],"actuated":[68],"using":[70,150],"machine":[71],"learning.":[72],"lights":[74],"sign":[75],"limited":[77],"number":[78],"combinations.":[81],"We":[82],"summarize":[83],"these":[84],"combinations":[85],"sets":[87],"obtain":[89],"feature":[91,110],"depicting":[92],"state.":[95],"This":[96],"paper":[97],"focuses":[98],"whether":[100],"inclusion":[102],"(estimated)":[105],"state":[106,158],"as":[107],"an":[108],"input":[109],"can":[111],"achieve":[112],"higher":[113,138],"accuracy":[114,139],"for":[115],"than":[122],"those":[123],"only":[125],"information.":[128],"Implementing":[129],"XGBoost":[130],"Bayesian":[132],"Networks,":[133],"found":[135],"that":[136],"lower":[142],"root":[143],"mean":[144],"square":[145],"error":[146],"achieved":[148],"by":[149],"states.":[151],"Whether":[152],"actual":[154],"or":[155],"estimated":[156],"next":[157],"improves":[159],"quality":[161],"prediction,":[164],"most":[166],"depends":[167],"degree":[170],"dependency":[173],"load":[176],"light.":[180]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}