{"id":"https://openalex.org/W4416749992","doi":"https://doi.org/10.1109/iros60139.2025.11247087","title":"DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models","display_name":"DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749992","doi":"https://doi.org/10.1109/iros60139.2025.11247087"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5102765458","display_name":"Shenyu Zhang","orcid":"https://orcid.org/0009-0006-4843-9794"},"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":"Shenyu Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031974859","display_name":"Jinfan Tian","orcid":"https://orcid.org/0000-0002-3610-6814"},"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":"Jiaguo Tian","raw_affiliation_strings":["Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019825437","display_name":"Zhengbang Zhu","orcid":"https://orcid.org/0009-0005-9310-3598"},"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":"Zhengbang Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101415286","display_name":"Shan Huang","orcid":"https://orcid.org/0000-0001-8837-6560"},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Huang","raw_affiliation_strings":["Chongqing Changan Automobile Co. Ltd,AI Laboratory,China,400023"],"affiliations":[{"raw_affiliation_string":"Chongqing Changan Automobile Co. Ltd,AI Laboratory,China,400023","institution_ids":["https://openalex.org/I4210131649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007483551","display_name":"Jucheng Yang","orcid":"https://orcid.org/0000-0002-5046-2663"},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jucheng Yang","raw_affiliation_strings":["Chongqing Changan Automobile Co. Ltd,AI Laboratory,China,400023"],"affiliations":[{"raw_affiliation_string":"Chongqing Changan Automobile Co. Ltd,AI Laboratory,China,400023","institution_ids":["https://openalex.org/I4210131649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"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":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Dept. of Computer Sci. and Eng.,Shanghai,China,200240","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102765458"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.6499,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75982287,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"10100","last_page":"10107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.592199981212616,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.592199981212616,"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/T10524","display_name":"Traffic control and management","score":0.0706000030040741,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.04569999873638153,"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/downstream","display_name":"Downstream (manufacturing)","score":0.6158000230789185},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5116999745368958},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4677000045776367},{"id":"https://openalex.org/keywords/waypoint","display_name":"Waypoint","score":0.44620001316070557},{"id":"https://openalex.org/keywords/taxis","display_name":"Taxis","score":0.44530001282691956},{"id":"https://openalex.org/keywords/headway","display_name":"Headway","score":0.37610000371932983},{"id":"https://openalex.org/keywords/air-traffic-control","display_name":"Air traffic control","score":0.3610999882221222},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.35929998755455017}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513999938964844},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.6158000230789185},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5116999745368958},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4677000045776367},{"id":"https://openalex.org/C2781271823","wikidata":"https://www.wikidata.org/wiki/Q138081","display_name":"Waypoint","level":2,"score":0.44620001316070557},{"id":"https://openalex.org/C183373512","wikidata":"https://www.wikidata.org/wiki/Q949618","display_name":"Taxis","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4253999888896942},{"id":"https://openalex.org/C2779240695","wikidata":"https://www.wikidata.org/wiki/Q4383682","display_name":"Headway","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C166961238","wikidata":"https://www.wikidata.org/wiki/Q221395","display_name":"Air traffic control","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C2778391309","wikidata":"https://www.wikidata.org/wiki/Q7832527","display_name":"Traffic simulation","level":3,"score":0.3305000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3237000107765198},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C2776777543","wikidata":"https://www.wikidata.org/wiki/Q1361182","display_name":"Air traffic management","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W6346207","https://openalex.org/W146964248","https://openalex.org/W610469435","https://openalex.org/W2190194936","https://openalex.org/W2339605857","https://openalex.org/W2903709398","https://openalex.org/W2963219401","https://openalex.org/W3098023203","https://openalex.org/W3133465684","https://openalex.org/W3179442871","https://openalex.org/W3181350748","https://openalex.org/W3203076355","https://openalex.org/W3207915602","https://openalex.org/W3209351137","https://openalex.org/W4221156702","https://openalex.org/W4308615108","https://openalex.org/W4361861254","https://openalex.org/W4383097675","https://openalex.org/W4383108225","https://openalex.org/W4383108456","https://openalex.org/W4383108499","https://openalex.org/W4385301318","https://openalex.org/W4386076338","https://openalex.org/W4388208052","https://openalex.org/W4391596770","https://openalex.org/W4391985078","https://openalex.org/W4392172801","https://openalex.org/W4394595621","https://openalex.org/W4401416425","https://openalex.org/W4402727068","https://openalex.org/W4403906447","https://openalex.org/W4404239715","https://openalex.org/W4409366385"],"related_works":[],"abstract_inverted_index":{"Microscopic":[0],"traffic":[1,50,59,193],"simulation":[2,51],"has":[3],"become":[4],"an":[5,143],"important":[6],"tool":[7],"for":[8,56,160,166],"autonomous":[9],"driving":[10,123,154,204],"training":[11],"and":[12,36,80,86,103,120,176],"testing.":[13],"Although":[14],"recent":[15],"data-driven":[16],"approaches":[17],"advance":[18],"realistic":[19],"behavior":[20],"generation,":[21],"their":[22,34],"learning":[23],"still":[24],"relies":[25],"primarily":[26],"on":[27],"a":[28,48,76,99,104],"single":[29],"real-world":[30],"dataset,":[31],"which":[32],"limits":[33],"diversity":[35,127],"thereby":[37],"hinders":[38],"downstream":[39,137],"algorithm":[40,155],"optimization.":[41],"In":[42],"this":[43,110],"paper,":[44],"we":[45,139],"propose":[46],"DriveGen,":[47],"novel":[49],"framework":[52],"with":[53,94],"large":[54,77,116,161],"models":[55,162],"more":[57],"diverse":[58],"generation":[60,147],"that":[61,149,172,190],"supports":[62],"further":[63,188],"customized":[64],"designs.":[65],"DriveGen":[66,113,195],"consists":[67],"of":[68,122,152,194,199,202,209],"two":[69],"internal":[70],"stages:":[71],"the":[72,89,153,164,191,200,207],"initialization":[73],"stage":[74,91],"uses":[75,150],"language":[78,101],"model":[79,102],"retrieval":[81],"technique":[82],"to":[83,183],"generate":[84],"map":[85],"vehicle":[87],"assets;":[88],"rollout":[90],"outputs":[92],"trajectories":[93],"selected":[95],"waypoint":[96],"goals":[97],"from":[98],"visual":[100],"specifically":[105],"designed":[106],"diffusion":[107],"planner.":[108],"Through":[109],"two-staged":[111],"process,":[112],"fully":[114],"utilizes":[115],"models\u2019":[117],"high-level":[118],"cognition":[119],"reasoning":[121],"behavior,":[124],"obtaining":[125],"greater":[126],"beyond":[128],"datasets":[129],"while":[130],"maintaining":[131],"high":[132],"realism.":[133],"To":[134],"support":[135],"effective":[136],"optimization,":[138],"additionally":[140],"develop":[141],"DriveGen-CS,":[142],"automatic":[144],"corner":[145,177],"case":[146],"pipeline":[148],"failures":[151],"as":[156],"additional":[157],"prompt":[158],"knowledge":[159],"without":[163],"need":[165],"retraining":[167],"or":[168],"fine-tuning.":[169],"Experiments":[170],"show":[171],"our":[173,210],"generated":[174],"scenarios":[175],"cases":[178],"have":[179],"superior":[180],"performance":[181,201],"compared":[182],"state-of-the-art":[184],"baselines.":[185],"Downstream":[186],"experiments":[187],"verify":[189],"synthesized":[192],"provides":[196],"better":[197],"optimization":[198],"typical":[203],"algorithms,":[205],"demonstrating":[206],"effectiveness":[208],"framework.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}
