{"id":"https://openalex.org/W4391769628","doi":"https://doi.org/10.1109/itsc57777.2023.10422358","title":"Predicting the Vehicle Turn-in Rates of Highway Service Area: A Random Forest Approach","display_name":"Predicting the Vehicle Turn-in Rates of Highway Service Area: A Random Forest Approach","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4391769628","doi":"https://doi.org/10.1109/itsc57777.2023.10422358"},"language":"en","primary_location":{"id":"doi:10.1109/itsc57777.2023.10422358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th 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/A5101184972","display_name":"Yubin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yubin Zheng","raw_affiliation_strings":["Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349403","display_name":"Cheng Cheng","orcid":"https://orcid.org/0000-0002-4367-0376"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Cheng","raw_affiliation_strings":["Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100989524","display_name":"Shui Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shui Yu","raw_affiliation_strings":["Hebei Province Expressway Jingxiong Management Center,Hebei Province,China,071799"],"affiliations":[{"raw_affiliation_string":"Hebei Province Expressway Jingxiong Management Center,Hebei Province,China,071799","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111832467","display_name":"Xian Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xian Ye","raw_affiliation_strings":["Jiaoke Transport Consultants LTD,Beijing,China,100083"],"affiliations":[{"raw_affiliation_string":"Jiaoke Transport Consultants LTD,Beijing,China,100083","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626962","display_name":"Xinghua Li","orcid":"https://orcid.org/0000-0003-3812-4271"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinghua Li","raw_affiliation_strings":["Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Tongji University,Key Laboratory of Road &#x0026; Traffic Engineering of Ministry of Education,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100398238","display_name":"Zixuan Wang","orcid":"https://orcid.org/0000-0001-5457-9554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zixuan Wang","raw_affiliation_strings":["Think Engine Management Consulting (Shanghai) Co., Ltd,Shanghai,China,200092"],"affiliations":[{"raw_affiliation_string":"Think Engine Management Consulting (Shanghai) Co., Ltd,Shanghai,China,200092","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101184972"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.3148,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58513161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1349","last_page":"1354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9395999908447266,"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":0.9395999908447266,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9243999719619751,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6419792771339417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.528806209564209},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.4290422201156616},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.42174485325813293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16094046831130981},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.15084975957870483},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13791635632514954},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.07768827676773071}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6419792771339417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.528806209564209},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.4290422201156616},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.42174485325813293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16094046831130981},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.15084975957870483},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13791635632514954},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.07768827676773071}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc57777.2023.10422358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th 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":18,"referenced_works":["https://openalex.org/W56701839","https://openalex.org/W1519043595","https://openalex.org/W1594031697","https://openalex.org/W2012249795","https://openalex.org/W2063660548","https://openalex.org/W2069929199","https://openalex.org/W2124717181","https://openalex.org/W2142131170","https://openalex.org/W2315859848","https://openalex.org/W2911964244","https://openalex.org/W2915809362","https://openalex.org/W2940485514","https://openalex.org/W3011726937","https://openalex.org/W4289518868","https://openalex.org/W4293525880","https://openalex.org/W4313639724","https://openalex.org/W4323256886","https://openalex.org/W6684773713"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W1924178503","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4308716060","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Vehicle":[0],"turn-in":[1,27,47,75,80,132,177],"rate":[2,28,76,81,133],"is":[3,99,138],"a":[4,57],"critical":[5],"metric":[6],"adopted":[7],"widely":[8],"in":[9,156,171],"highway":[10],"service":[11,18],"area":[12],"(HSA)":[13],"location":[14],"selection,":[15],"design,":[16],"and":[17,36,72,91,111,129,140,146,174],"provision.":[19],"Previous":[20],"on-site":[21],"investigations":[22],"have":[23,40],"revealed":[24],"that":[25,164],"the":[26,53,116,119,124,135,149,157,165],"varies":[29],"significantly":[30],"among":[31,148],"HSAs.":[32,181],"Although":[33],"some":[34],"parametric":[35],"nonparametric":[37],"learning":[38],"methods":[39],"been":[41],"implemented":[42],"for":[43,69,88],"predicting":[44],"HSA":[45,70],"vehicle":[46,74,131,176],"rates,":[48],"current":[49],"research":[50],"seldom":[51],"tests":[52],"prediction":[54,98,167],"feasibility":[55],"via":[56,102],"random":[58],"forest":[59],"(RF)":[60],"model.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"proposed":[66],"RF":[67,125,166],"models":[68],"passenger":[71,128,173],"freight":[73,130,175],"predictions.":[77],"210":[78],"HSAs":[79],"samples":[82],"are":[83],"used":[84],"from":[85],"Sichuan,":[86],"China":[87],"model":[89,97,126,168],"calibration":[90],"validation.":[92],"A":[93],"comparative":[94],"analysis":[95],"of":[96,123,134,180],"further":[100],"conducted":[101],"support":[103],"vector":[104],"regression,":[105,108],"k-Nearest":[106],"Neighbor":[107],"RF,":[109],"XGBoost,":[110],"AdaBoost":[112],"method.":[113],"Compared":[114],"with":[115],"rest":[117],"models,":[118],"mean":[120],"absolute":[121],"error":[122],"on":[127],"validation":[136],"dataset":[137],"2.36%":[139],"2.92%":[141],"respectively,":[142],"which":[143],"rank":[144],"first":[145],"second":[147],"tested":[150],"models.":[151],"It":[152],"also":[153],"performs":[154,169],"well":[155,170],"other":[158],"two":[159],"measurements.":[160],"The":[161],"results":[162],"indicate":[163],"both":[172],"rates":[178],"estimation":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
