{"id":"https://openalex.org/W2151541288","doi":"https://doi.org/10.1109/itsc.2007.4357757","title":"An Improved Evidential Fusion Approach for Real-time Urban Link Speed Estimation","display_name":"An Improved Evidential Fusion Approach for Real-time Urban Link Speed Estimation","publication_year":2007,"publication_date":"2007-09-01","ids":{"openalex":"https://openalex.org/W2151541288","doi":"https://doi.org/10.1109/itsc.2007.4357757","mag":"2151541288"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2007.4357757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2007.4357757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Intelligent Transportation Systems Conference","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/A5101735181","display_name":"Qing\u2010Jie Kong","orcid":"https://orcid.org/0000-0002-3788-305X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing-jie Kong","raw_affiliation_strings":["School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070290221","display_name":"Yikai Chen","orcid":"https://orcid.org/0000-0002-5193-9849"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yikai Chen","raw_affiliation_strings":["School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061110835","display_name":"Yuncai Liu","orcid":"https://orcid.org/0000-0002-4040-4478"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuncai Liu","raw_affiliation_strings":["School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Information, and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101735181"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.7168,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86484521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"32","issue":null,"first_page":"562","last_page":"567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.998199999332428,"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":0.998199999332428,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9850999712944031,"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/T11106","display_name":"Data Management and Algorithms","score":0.9819999933242798,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7522865533828735},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.7241033315658569},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6746921539306641},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.6452469825744629},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6101565361022949},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5872211456298828},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.4869171380996704},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4356318712234497},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3126095235347748}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7522865533828735},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.7241033315658569},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6746921539306641},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.6452469825744629},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6101565361022949},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5872211456298828},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4869171380996704},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4356318712234497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3126095235347748},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2007.4357757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2007.4357757","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Intelligent Transportation Systems Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W894767924","https://openalex.org/W1561128958","https://openalex.org/W1993853885","https://openalex.org/W1995435811","https://openalex.org/W2014330307","https://openalex.org/W2015953248","https://openalex.org/W2027665506","https://openalex.org/W2074160172","https://openalex.org/W2093639153","https://openalex.org/W2099319707","https://openalex.org/W2101560629","https://openalex.org/W2101641738","https://openalex.org/W2117079761","https://openalex.org/W2120307319","https://openalex.org/W2159160074","https://openalex.org/W2160407179","https://openalex.org/W2361784260","https://openalex.org/W2403746960","https://openalex.org/W2406470551","https://openalex.org/W2538988013","https://openalex.org/W2797148637","https://openalex.org/W4301347335","https://openalex.org/W6633752984","https://openalex.org/W6675607698","https://openalex.org/W6677739455"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2586280620","https://openalex.org/W2805505483","https://openalex.org/W2334071950","https://openalex.org/W2384744344","https://openalex.org/W4233932308","https://openalex.org/W1799694159","https://openalex.org/W2393169196","https://openalex.org/W2366610330","https://openalex.org/W1550496571"],"abstract_inverted_index":{"On":[0],"the":[1,27,30,36,51,59,67,71,79,85,103,106,112],"basis":[2],"of":[3,29,35,54,84,105,118],"previous":[4,31,113],"researches,":[5],"an":[6,128],"improved":[7,44],"evidential":[8],"fusion":[9],"approach":[10,87],"is":[11,43],"presented":[12],"to":[13,49,101],"integrate":[14],"heterogeneous":[15],"multi-sensor":[16],"data":[17,97,117],"in":[18,33,109,133],"Urban":[19],"Advanced":[20],"Traveler":[21],"Information":[22],"Systems.":[23],"The":[24,115],"method":[25,108],"inherits":[26],"advantages":[28],"model":[32],"terms":[34],"real-time":[37],"processing":[38],"feature;":[39],"meanwhile,":[40],"its":[41],"performance":[42],"by":[45],"adding":[46],"a":[47,91,95],"mechanism":[48],"evaluate":[50],"dynamic":[52,72],"reliability":[53,62],"sensors.":[55],"In":[56],"this":[57],"paper,":[58],"whole":[60],"evidence":[61],"algorithms,":[63],"which":[64],"contain":[65],"both":[66],"static":[68],"one":[69],"and":[70,81,94,121],"one,":[73],"are":[74,88,99],"provided":[75],"primarily.":[76],"After":[77],"that,":[78],"frame":[80],"computational":[82],"procedures":[83],"new":[86],"given.":[89],"Finally,":[90],"simulation":[92],"test":[93],"real-world":[96,116],"experiment":[98],"discussed":[100],"explain":[102],"advantage":[104],"proposed":[107],"comparison":[110],"with":[111],"model.":[114],"loop":[119],"detectors":[120],"GPS":[122],"probe":[123],"vehicles":[124],"were":[125],"collected":[126],"from":[127],"urban":[129],"arterial":[130],"road":[131],"section":[132],"Shanghai.":[134]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}