{"id":"https://openalex.org/W3030034795","doi":"https://doi.org/10.1109/itsc45102.2020.9294567","title":"Injury Severity Analysis of Secondary Incidents","display_name":"Injury Severity Analysis of Secondary Incidents","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3030034795","doi":"https://doi.org/10.1109/itsc45102.2020.9294567","mag":"3030034795"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd 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/A5100336958","display_name":"Jing Li","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":"Jing Li","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021982777","display_name":"Jingqiu Guo","orcid":"https://orcid.org/0000-0002-7378-3101"},"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":"Jingqiu Guo","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101927713","display_name":"Min Qiu","orcid":"https://orcid.org/0000-0002-9472-4514"},"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":"Min Qiu","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100336958"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06775528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.9965000152587891,"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/T11824","display_name":"Injury Epidemiology and Prevention","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6246835589408875},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6033536195755005},{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.509800136089325},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4815973937511444},{"id":"https://openalex.org/keywords/poison-control","display_name":"Poison control","score":0.4381183385848999},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.42510032653808594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4068150520324707},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3269495666027069},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2578497529029846},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2540803849697113},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.20082035660743713},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1578224003314972},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14682671427726746}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6246835589408875},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6033536195755005},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.509800136089325},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4815973937511444},{"id":"https://openalex.org/C3017944768","wikidata":"https://www.wikidata.org/wiki/Q1450463","display_name":"Poison control","level":2,"score":0.4381183385848999},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.42510032653808594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4068150520324707},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3269495666027069},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2578497529029846},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2540803849697113},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.20082035660743713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1578224003314972},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14682671427726746},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.5699999928474426,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W34176136","https://openalex.org/W118202324","https://openalex.org/W1541797976","https://openalex.org/W1554944419","https://openalex.org/W1964887383","https://openalex.org/W1993292974","https://openalex.org/W2022714541","https://openalex.org/W2047194874","https://openalex.org/W2071610949","https://openalex.org/W2083133775","https://openalex.org/W2095769804","https://openalex.org/W2169556851","https://openalex.org/W2195989306","https://openalex.org/W2292045100","https://openalex.org/W2293618063","https://openalex.org/W2333130800","https://openalex.org/W2501609357","https://openalex.org/W2508952991","https://openalex.org/W2527905620","https://openalex.org/W2593065359","https://openalex.org/W2604266906","https://openalex.org/W2731895752","https://openalex.org/W2782536475","https://openalex.org/W2792180719","https://openalex.org/W2844643373","https://openalex.org/W2896236534","https://openalex.org/W2899037650","https://openalex.org/W2910606032","https://openalex.org/W2914570919","https://openalex.org/W2923982851","https://openalex.org/W2931789502","https://openalex.org/W2944278099","https://openalex.org/W2945255483","https://openalex.org/W2950242191","https://openalex.org/W2960860747","https://openalex.org/W2972231051","https://openalex.org/W2976036462","https://openalex.org/W2988595664","https://openalex.org/W2996145150","https://openalex.org/W3005147439","https://openalex.org/W3012140785","https://openalex.org/W3021428299","https://openalex.org/W3157146611","https://openalex.org/W3215186461","https://openalex.org/W6604820115","https://openalex.org/W6632595481","https://openalex.org/W6702657675","https://openalex.org/W6735705496","https://openalex.org/W6749179253","https://openalex.org/W6761528492"],"related_works":["https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W4224941037","https://openalex.org/W2004826645","https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W1517228774","https://openalex.org/W2767419625","https://openalex.org/W2389704471"],"abstract_inverted_index":{"Compared":[0],"to":[1,9,22,75,146,148,173],"normal":[2],"incidents,":[3],"secondary":[4,30,152,179],"incidents":[5],"are":[6],"more":[7],"likely":[8],"result":[10],"in":[11,38,165],"severe":[12],"injuries":[13],"and":[14,52,85,140,162,168],"fatalities.":[15],"However,":[16],"limited":[17,114],"efforts":[18],"have":[19,170],"been":[20],"made":[21],"unveil":[23],"the":[24,27,36,77,95,102,121,127,171],"factors":[25],"affecting":[26],"severity":[28,129,150],"of":[29,79,123,137,142,151],"incidents.":[31,153,180],"Incidents":[32],"that":[33,101],"occurred":[34],"on":[35,94,126],"Interstate-5":[37],"California":[39],"within":[40],"five":[41],"years":[42],"were":[43,55,73,90,144],"collected.":[44],"Detailed":[45],"real-time":[46],"traffic":[47,156],"flow":[48],"conditions,":[49],"geometric":[50],"characteristics,":[51],"weather":[53],"conditions":[54,157],"obtained.":[56],"First,":[57],"a":[58,106],"Random":[59],"Forest-based":[60],"(RF)":[61],"feature":[62],"selection":[63],"approach":[64],"was":[65,99],"adopted.":[66],"Then,":[67],"Support":[68],"Vector":[69],"Machine":[70],"(SVM)":[71],"models":[72,89],"developed":[74],"investigate":[76],"effects":[78],"contributing":[80],"factors.":[81],"For":[82],"comparison,":[83],"RF":[84],"Ordered":[86],"Logistic":[87],"(OL)":[88],"also":[91],"built":[92],"based":[93],"same":[96],"dataset.":[97],"It":[98],"found":[100,145],"SVM":[103],"model":[104],"has":[105],"high":[107],"capacity":[108],"for":[109],"solving":[110],"classification":[111],"problems":[112],"with":[113],"data":[115],"availability.":[116],"Further,":[117],"sensitivity":[118],"analysis":[119],"assessed":[120],"impacts":[122],"explanatory":[124],"variables":[125],"injury":[128,149],"level.":[130],"Explanatory":[131],"variables,":[132],"including":[133],"occupancy,":[134],"duration,":[135],"frequency":[136],"lanes":[138],"changes,":[139],"number":[141],"lanes,":[143],"contribute":[147],"Smoothing":[154],"these":[155],"after":[158],"an":[159],"incident":[160,166],"occurs":[161],"responding":[163],"fast":[164],"handling":[167],"clearance":[169],"potential":[172],"reduce":[174],"road":[175],"trauma":[176],"caused":[177],"by":[178]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
