{"id":"https://openalex.org/W4408712124","doi":"https://doi.org/10.1109/itsc58415.2024.10919503","title":"Real-Time Optimization-Based Path Planning for Autonomous Semi-Trailer Trucks*","display_name":"Real-Time Optimization-Based Path Planning for Autonomous Semi-Trailer Trucks*","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4408712124","doi":"https://doi.org/10.1109/itsc58415.2024.10919503"},"language":"en","primary_location":{"id":"doi:10.1109/itsc58415.2024.10919503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10919503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th 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/A5054450699","display_name":"Pengtao Ma","orcid":"https://orcid.org/0000-0003-1826-0751"},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengtao Ma","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090401330","display_name":"Lei Sun","orcid":"https://orcid.org/0000-0002-5246-1373"},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Sun","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shouyang Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouyang Wei","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Diana Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Diana Wan","raw_affiliation_strings":["University of British Columbia,Vancouver,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of British Columbia,Vancouver,Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100717860","display_name":"Feng Ding","orcid":"https://orcid.org/0000-0001-9153-9279"},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Ding","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038388335","display_name":"Donghao Zhang","orcid":"https://orcid.org/0000-0001-5663-6372"},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghao Zhang","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shan Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I2801441622","display_name":"China Railway Corporation","ror":"https://ror.org/044wv3489","country_code":"CN","type":"government","lineage":["https://openalex.org/I2801441622","https://openalex.org/I4210122102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Tian","raw_affiliation_strings":["DeepWay Corporation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepWay Corporation,Beijing,China","institution_ids":["https://openalex.org/I2801441622"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4087,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63708589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3133","last_page":"3140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T11615","display_name":"Control and Dynamics of Mobile Robots","score":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.7943553924560547},{"id":"https://openalex.org/keywords/trailer","display_name":"Trailer","score":0.7702803611755371},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6286296248435974},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6009551882743835},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5140491724014282},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.22998669743537903},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1928795874118805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1723928451538086},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1232428252696991},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.11813423037528992}],"concepts":[{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.7943553924560547},{"id":"https://openalex.org/C2779101595","wikidata":"https://www.wikidata.org/wiki/Q7832787","display_name":"Trailer","level":2,"score":0.7702803611755371},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6286296248435974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6009551882743835},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5140491724014282},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.22998669743537903},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1928795874118805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1723928451538086},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1232428252696991},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.11813423037528992}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc58415.2024.10919503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10919503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th 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":19,"referenced_works":["https://openalex.org/W2005126631","https://openalex.org/W2013439434","https://openalex.org/W2082142320","https://openalex.org/W2107338474","https://openalex.org/W2129469913","https://openalex.org/W2406067508","https://openalex.org/W2606365885","https://openalex.org/W2769646558","https://openalex.org/W2793066675","https://openalex.org/W2967606622","https://openalex.org/W3101798601","https://openalex.org/W3118675683","https://openalex.org/W3120638006","https://openalex.org/W3155272911","https://openalex.org/W3156277031","https://openalex.org/W4286285630","https://openalex.org/W4312927314","https://openalex.org/W4376166839","https://openalex.org/W4386995827"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1978510931","https://openalex.org/W2359600231","https://openalex.org/W2380019117","https://openalex.org/W3138952546","https://openalex.org/W1987886368","https://openalex.org/W1660309994","https://openalex.org/W2369187583","https://openalex.org/W3197207153"],"abstract_inverted_index":{"Autonomous":[0],"semi-trailer":[1,51,214],"trucks":[2,52],"have":[3],"great":[4],"potential":[5],"to":[6,24,31,56,85,172],"offer":[7],"safer":[8],"and":[9,35,64,70,102,129,135,162,212,226,243],"more":[10,108],"efficient":[11,225],"transportation.":[12],"Path":[13],"planning":[14,83],"is":[15,53,127,194,224],"an":[16,26,47,154],"important":[17],"part":[18],"of":[19,99,116,139,206,240],"autonomous":[20],"driving,":[21],"which":[22,141],"aims":[23],"generate":[25],"optimal":[27,48],"path":[28,49,82,110],"for":[29,50,113,228],"vehicles":[30],"avoid":[32],"collision":[33,159],"risks":[34],"keep":[36],"them":[37],"as":[38,43],"centered":[39],"in":[40,178,238],"the":[41,57,60,65,93,117,137,169,175,204,207,221,235],"lane":[42,164,176,244],"possible.":[44],"However,":[45],"achieving":[46],"challenging":[54],"due":[55],"complex":[58],"kinematics,":[59],"large":[61],"vehicle":[62,236],"dimensions":[63],"trade-off":[66],"between":[67],"model":[68,106],"complexity":[69],"real-time":[71,80,229],"capability.":[72],"In":[73],"this":[74],"work,":[75],"we":[76,152],"propose":[77],"a":[78],"novel":[79],"optimization-based":[81],"method":[84,209,223],"address":[86],"these":[87],"problems.":[88],"This":[89,104,167],"approach":[90],"involves":[91],"modeling":[92,126,149],"entire":[94],"tractor-trailer":[95],"system":[96],"with":[97,146,157,210],"positioning":[98],"all":[100,122],"axles":[101],"corners.":[103],"detailed":[105],"enables":[107],"accurate":[109,227],"planning,":[111],"allowing":[112],"full":[114],"utilization":[115],"drivable":[118],"space":[119],"while":[120],"satisfying":[121],"physical":[123],"constraints.":[124],"The":[125,191,217],"approximated":[128],"simplified":[130],"by":[131],"assuming":[132],"equal":[133],"curvature":[134],"using":[136,196],"law":[138],"cosines,":[140],"greatly":[142],"reduces":[143],"computation":[144],"burden":[145],"slightly":[147],"sacrificing":[148],"accuracy.":[150],"Then":[151],"construct":[153],"optimization":[155,192],"problem":[156,193],"strict":[158],"avoidance":[160,242],"constraints":[161],"soft":[163],"centering":[165],"preferences.":[166],"allows":[168],"truck's":[170],"wheels":[171],"temporarily":[173],"exceed":[174],"boundaries":[177],"certain":[179],"scenarios":[180],"like":[181],"tight":[182],"bends":[183],"or":[184],"narrow":[185],"roads,":[186],"improving":[187],"its":[188],"passing":[189],"ability.":[190],"solved":[195],"high-efficient":[197],"Augmented":[198],"Lagrange":[199],"Multiplier":[200],"method.":[201],"We":[202],"demonstrate":[203],"performance":[205],"proposed":[208,222],"simulations":[211],"real":[213],"truck":[215],"experiments.":[216],"results":[218],"show":[219],"that":[220],"application.":[230],"It":[231],"can":[232],"significantly":[233],"improve":[234],"behavior":[237],"terms":[239],"obstacle":[241],"centering.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
