{"id":"https://openalex.org/W3011313639","doi":"https://doi.org/10.1109/cdc40024.2019.9029216","title":"Stop-and-go wave dissipation using accumulated controlled moving bottlenecks in multi-class CTM framework","display_name":"Stop-and-go wave dissipation using accumulated controlled moving bottlenecks in multi-class CTM framework","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3011313639","doi":"https://doi.org/10.1109/cdc40024.2019.9029216","mag":"3011313639"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9029216","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","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/A5000499208","display_name":"Mladen \u010ci\u010di\u0107","orcid":"https://orcid.org/0000-0002-4472-6298"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Mladen Cicic","raw_affiliation_strings":["Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045975901","display_name":"Karl Henrik Johansson","orcid":"https://orcid.org/0000-0001-9940-5929"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Karl Henrik Johansson","raw_affiliation_strings":["Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of Decision and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000499208"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":1.9958,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.87229305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":1.0,"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":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991999864578247,"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/bottleneck","display_name":"Bottleneck","score":0.8682961463928223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7013626098632812},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6065723896026611},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4641149640083313},{"id":"https://openalex.org/keywords/rest","display_name":"Rest (music)","score":0.46121418476104736},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.4338458478450775},{"id":"https://openalex.org/keywords/traffic-wave","display_name":"Traffic wave","score":0.4199192523956299},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.35725080966949463},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.32734358310699463},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.27204644680023193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22592505812644958},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21945855021476746},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1855367124080658},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15756219625473022},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.1446136236190796},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.12381923198699951}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8682961463928223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7013626098632812},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6065723896026611},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4641149640083313},{"id":"https://openalex.org/C77265313","wikidata":"https://www.wikidata.org/wiki/Q879844","display_name":"Rest (music)","level":2,"score":0.46121418476104736},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4338458478450775},{"id":"https://openalex.org/C168069670","wikidata":"https://www.wikidata.org/wiki/Q2596069","display_name":"Traffic wave","level":4,"score":0.4199192523956299},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35725080966949463},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.32734358310699463},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.27204644680023193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22592505812644958},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21945855021476746},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1855367124080658},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15756219625473022},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.1446136236190796},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.12381923198699951},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc40024.2019.9029216","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1778418663","https://openalex.org/W1992924916","https://openalex.org/W2008102069","https://openalex.org/W2022706483","https://openalex.org/W2037141248","https://openalex.org/W2047175273","https://openalex.org/W2123362463","https://openalex.org/W2330358296","https://openalex.org/W2549608017","https://openalex.org/W2561374312","https://openalex.org/W2611350544","https://openalex.org/W2766693351","https://openalex.org/W2969124619","https://openalex.org/W3121317743","https://openalex.org/W6628982836"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W3106071504","https://openalex.org/W591177459","https://openalex.org/W2520590435","https://openalex.org/W1129591933","https://openalex.org/W301804496","https://openalex.org/W4254844281","https://openalex.org/W2754256240"],"abstract_inverted_index":{"Stop-and-go":[0],"waves":[1,133],"on":[2],"freeways":[3],"are":[4,30,95,128],"a":[5,72,120],"well":[6],"known":[7],"problem":[8],"that":[9],"has":[10],"typically":[11],"been":[12],"addressed":[13],"using":[14,60],"dynamic":[15],"speed":[16],"limits.":[17],"As":[18],"connected":[19],"automated":[20,51],"vehicles":[21,43,52,82,102],"enter":[22],"the":[23,34,55,58,77,80,84,88,92,112,115,136,140,145],"roads,":[24],"new":[25],"approaches":[26],"to":[27,41,49,75,97,110,130],"traffic":[28,61,116],"control":[29,35],"becoming":[31],"available,":[32],"since":[33],"actions":[36],"can":[37],"now":[38],"be":[39],"communicated":[40],"these":[42],"directly.":[44],"It":[45],"is":[46,147],"therefore":[47],"important":[48],"consider":[50],"independently":[53],"from":[54],"rest":[56,113],"of":[57,91,114,144],"traffic,":[59],"models":[62],"with":[63],"multiple":[64],"vehicle":[65],"classes.":[66],"In":[67,124],"this":[68,125],"paper,":[69],"we":[70,94,127],"use":[71,108],"multi-class":[73],"CTM":[74],"capture":[76],"interaction":[78],"between":[79],"controlled":[81,101,121],"and":[83,106,138],"background":[85],"traffic.":[86,141],"Exploiting":[87],"nonlinear":[89],"nature":[90],"model,":[93],"able":[96,129],"first":[98],"collect":[99],"enough":[100],"into":[103],"an":[104],"area,":[105],"then":[107],"them":[109],"actuate":[111],"by":[117],"acting":[118],"as":[119],"moving":[122],"bottleneck.":[123],"way,":[126],"dissipate":[131],"stop-and-go":[132],"quicker,":[134],"improving":[135],"throughput":[137],"homogenizing":[139],"The":[142],"effectiveness":[143],"approach":[146],"demonstrated":[148],"in":[149],"simulations.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
