{"id":"https://openalex.org/W2964749398","doi":"https://doi.org/10.1145/3292500.3330949","title":"PressLight","display_name":"PressLight","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2964749398","doi":"https://doi.org/10.1145/3292500.3330949","mag":"2964749398"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330949","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330949","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330949","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330949","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100777770","display_name":"Hua Wei","orcid":"https://orcid.org/0000-0002-3735-1635"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hua Wei","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028711697","display_name":"Chacha Chen","orcid":null},"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":"Chacha Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105507434","display_name":"Guanjie Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guanjie Zheng","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368801","display_name":"Kan Wu","orcid":"https://orcid.org/0000-0002-8306-5066"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kan Wu","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003021595","display_name":"Vikash V. Gayah","orcid":"https://orcid.org/0000-0002-0648-3360"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vikash Gayah","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076970762","display_name":"Kai Xu","orcid":"https://orcid.org/0000-0002-1387-2786"},"institutions":[{"id":"https://openalex.org/I4210133666","display_name":"Tiandi Science & Technology (China)","ror":"https://ror.org/03ssr6t63","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Xu","raw_affiliation_strings":["Shanghai Tianrang Intelligent Technology Co., Ltd, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Tianrang Intelligent Technology Co., Ltd, Shanghai, China","institution_ids":["https://openalex.org/I4210133666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016516907","display_name":"Zhenhui Li","orcid":"https://orcid.org/0000-0001-7221-2588"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenhui Li","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100777770"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":16.3399,"has_fulltext":true,"cited_by_count":354,"citation_normalized_percentile":{"value":0.99450674,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1290","last_page":"1298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9948999881744385,"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":0.9945999979972839,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.814069390296936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768549919128418},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.7315493822097778},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5211889147758484},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4790462255477905},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4768834710121155},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4566679298877716},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44465380907058716},{"id":"https://openalex.org/keywords/roundabout","display_name":"Roundabout","score":0.4278806149959564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42027148604393005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33778929710388184},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14225167036056519},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1091429591178894},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.10676968097686768}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.814069390296936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768549919128418},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.7315493822097778},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5211889147758484},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4790462255477905},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4768834710121155},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4566679298877716},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44465380907058716},{"id":"https://openalex.org/C109157449","wikidata":"https://www.wikidata.org/wiki/Q7371221","display_name":"Roundabout","level":2,"score":0.4278806149959564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42027148604393005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33778929710388184},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14225167036056519},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1091429591178894},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.10676968097686768},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330949","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330949","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330949","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3292500.3330949","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330949","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330949","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1035053891","display_name":null,"funder_award_id":"1639150","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4098986844","display_name":null,"funder_award_id":"1652525","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4342645261","display_name":null,"funder_award_id":"1618448","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964749398.pdf","grobid_xml":"https://content.openalex.org/works/W2964749398.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W5525483","https://openalex.org/W33871791","https://openalex.org/W578827907","https://openalex.org/W1496467067","https://openalex.org/W1595704756","https://openalex.org/W1998622835","https://openalex.org/W2007894170","https://openalex.org/W2022686149","https://openalex.org/W2057786298","https://openalex.org/W2074500080","https://openalex.org/W2088595989","https://openalex.org/W2124657875","https://openalex.org/W2145339207","https://openalex.org/W2149012699","https://openalex.org/W2230788120","https://openalex.org/W2415391098","https://openalex.org/W2498017881","https://openalex.org/W2549048496","https://openalex.org/W2809148419","https://openalex.org/W2944397927","https://openalex.org/W2945991855","https://openalex.org/W3105017587"],"related_works":["https://openalex.org/W2093826578","https://openalex.org/W4294237266","https://openalex.org/W3195565206","https://openalex.org/W647040144","https://openalex.org/W2176704059","https://openalex.org/W3118850949","https://openalex.org/W4375811566","https://openalex.org/W53329137","https://openalex.org/W2040382538","https://openalex.org/W4256628538"],"abstract_inverted_index":{"Traffic":[0],"signal":[1,51],"control":[2],"is":[3,103,122],"essential":[4],"for":[5,47],"transportation":[6,25,99,114,179],"efficiency":[7],"in":[8,21,67,73,98,112,128],"road":[9],"networks.":[10],"It":[11],"has":[12],"been":[13],"a":[14,68,78],"challenging":[15],"problem":[16],"because":[17],"of":[18,87,119,139,163],"the":[19,29,59,84,106,113,126,137,140,145,161,164],"complexity":[20],"traffic":[22,35,50,141],"dynamics.":[23],"Conventional":[24],"research":[26],"suffers":[27],"from":[28],"incompetency":[30],"to":[31,33,40,45,92,134],"adapt":[32],"dynamic":[34],"situations.":[36],"Recent":[37],"studies":[38,57,97],"propose":[39,91],"use":[41],"reinforcement":[42],"learning":[43,80],"(RL)":[44],"search":[46],"more":[48],"efficient":[49],"plans.":[52],"However,":[53],"most":[54],"existing":[55,182],"RL-based":[56],"design":[58,86,118],"key":[60],"elements":[61],"-":[62,66],"reward":[63,117,166],"and":[64,77,181],"state":[65,156],"heuristic":[69,85],"way.":[70],"This":[71],"results":[72],"highly":[74],"sensitive":[75],"performances":[76],"long":[79],"process.":[81],"To":[82],"avoid":[83],"RL":[88,94],"elements,":[89],"we":[90,171],"connect":[93],"with":[95],"recent":[96],"research.":[100],"Our":[101],"method":[102,108,121,175],"inspired":[104],"by":[105,125],"state-of-the-art":[107],"max":[109],"pressure":[110],"(MP)":[111],"field.":[115],"The":[116],"our":[120,154,174],"well":[123],"supported":[124],"theory":[127],"MP,":[129],"which":[130],"can":[131,158],"be":[132,135],"proved":[133],"maximizing":[136],"throughput":[138],"network,":[142],"i.e.,":[143],"minimizing":[144],"overall":[146],"network":[147],"travel":[148],"time.":[149],"We":[150],"also":[151],"show":[152],"that":[153,173],"concise":[155],"representation":[157],"fully":[159],"support":[160],"optimization":[162],"proposed":[165],"function.":[167],"Through":[168],"comprehensive":[169],"experiments,":[170],"demonstrate":[172],"outperforms":[176],"both":[177],"conventional":[178],"approaches":[180],"learning-based":[183],"methods.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":84},{"year":2024,"cited_by_count":84},{"year":2023,"cited_by_count":68},{"year":2022,"cited_by_count":50},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":3}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2019-08-13T00:00:00"}