{"id":"https://openalex.org/W4387847253","doi":"https://doi.org/10.1145/3583780.3615098","title":"Understanding and Modeling Collision Avoidance Behavior for Realistic Crowd Simulation","display_name":"Understanding and Modeling Collision Avoidance Behavior for Realistic Crowd Simulation","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387847253","doi":"https://doi.org/10.1145/3583780.3615098"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615098","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615098","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615098","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","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/10.1145/3583780.3615098","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102947902","display_name":"Zihan Yu","orcid":"https://orcid.org/0000-0001-8439-7583"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihan Yu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085160493","display_name":"Guozhen Zhang","orcid":"https://orcid.org/0000-0003-0592-2285"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozhen Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044100655","display_name":"Depeng Jin","orcid":"https://orcid.org/0000-0003-0419-5514"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Depeng Jin","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102947902"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.3915,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61321851,"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":"3052","last_page":"3061"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9965999722480774,"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/T10370","display_name":"Traffic and Road Safety","score":0.9947999715805054,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.8502489328384399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7771461009979248},{"id":"https://openalex.org/keywords/crowd-simulation","display_name":"Crowd simulation","score":0.7164739966392517},{"id":"https://openalex.org/keywords/crowd-psychology","display_name":"Crowd psychology","score":0.5860377550125122},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5516003966331482},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5406448841094971},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.5161715149879456},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4670509397983551},{"id":"https://openalex.org/keywords/collision-detection","display_name":"Collision detection","score":0.46396127343177795},{"id":"https://openalex.org/keywords/modeling-and-simulation","display_name":"Modeling and simulation","score":0.46276941895484924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3810679614543915},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.37624749541282654},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.12686702609062195},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1015113890171051},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08844718337059021}],"concepts":[{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.8502489328384399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7771461009979248},{"id":"https://openalex.org/C45617602","wikidata":"https://www.wikidata.org/wiki/Q465266","display_name":"Crowd simulation","level":3,"score":0.7164739966392517},{"id":"https://openalex.org/C44042526","wikidata":"https://www.wikidata.org/wiki/Q1355183","display_name":"Crowd psychology","level":2,"score":0.5860377550125122},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5516003966331482},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5406448841094971},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.5161715149879456},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4670509397983551},{"id":"https://openalex.org/C199668693","wikidata":"https://www.wikidata.org/wiki/Q1550329","display_name":"Collision detection","level":3,"score":0.46396127343177795},{"id":"https://openalex.org/C167343916","wikidata":"https://www.wikidata.org/wiki/Q6888384","display_name":"Modeling and simulation","level":2,"score":0.46276941895484924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3810679614543915},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.37624749541282654},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.12686702609062195},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1015113890171051},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08844718337059021},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3615098","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615098","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615098","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583780.3615098","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615098","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615098","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2437064176","display_name":null,"funder_award_id":"U21B2036","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3188007771","display_name":null,"funder_award_id":"U20B2060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G949793273","display_name":null,"funder_award_id":"2022YFF0606904","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329777","display_name":"Beijing National Research Center For Information Science And Technology","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387847253.pdf","grobid_xml":"https://content.openalex.org/works/W4387847253.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1481791336","https://openalex.org/W2002440441","https://openalex.org/W2071723021","https://openalex.org/W2167052694","https://openalex.org/W2463843416","https://openalex.org/W2794996069","https://openalex.org/W2899629811","https://openalex.org/W2989637561","https://openalex.org/W3022916097","https://openalex.org/W3033920763","https://openalex.org/W3043995842","https://openalex.org/W3106257603","https://openalex.org/W3108908812","https://openalex.org/W3166747893","https://openalex.org/W3206124495","https://openalex.org/W4200085643","https://openalex.org/W4248343126","https://openalex.org/W4283696437","https://openalex.org/W4290875130","https://openalex.org/W4300672471","https://openalex.org/W4321648808","https://openalex.org/W4367047458"],"related_works":["https://openalex.org/W2280250567","https://openalex.org/W3114736933","https://openalex.org/W2189920449","https://openalex.org/W2145709447","https://openalex.org/W3096912411","https://openalex.org/W1555506539","https://openalex.org/W2347937906","https://openalex.org/W2158902531","https://openalex.org/W2172235251","https://openalex.org/W3043995842"],"abstract_inverted_index":{"For":[0],"walking":[1,38],"pedestrians,":[2,11],"when":[3,253],"they":[4,12],"are":[5,45,173],"blocked":[6],"by":[7,132,202],"obstacles":[8],"or":[9,76],"other":[10],"adjust":[13],"their":[14],"speeds":[15],"and":[16,40,43,103,151,205,245,263],"directions":[17],"to":[18,48,69,84,100,114,155,177,250],"avoid":[19],"colliding":[20],"with":[21,231],"them,":[22],"which":[23,52,82,194],"is":[24,31,147,152,261],"called":[25],"collision":[26,74,106,117,167,199,268],"avoidance":[27,107,118,168,200,269],"behavior.":[28,169],"This":[29,208],"behavior":[30,75,108,119,146,201,270],"the":[32,46,55,66,72,91,105,134,137,145,179,191,196,213,272],"most":[33,61],"complex":[34,73],"part":[35],"of":[36,88,90,181,198,215,241],"pedestrians'":[37,238],"processes":[39],"its":[41,203],"modeling":[42],"simulation":[44],"keys":[47],"realistic":[49,95,219,266],"crowd":[50,96,220],"simulation,":[51,97,221],"serves":[53],"as":[54],"foundation":[56,214],"for":[57,120,165,218],"various":[58],"applications.":[59],"However,":[60],"existing":[62],"methods":[63],"either":[64],"lack":[65],"representation":[67],"power":[68],"accurately":[70],"model":[71,79,104,260],"do":[77],"not":[78],"it":[80,131],"explicitly,":[81],"leads":[83],"a":[85,110,125,141,162,185,224],"poor":[86],"level":[87,180],"realism":[89,197],"simulation.":[92],"To":[93],"realize":[94],"we":[98,123,183,222],"propose":[99,124,184],"analyze,":[101],"understand,":[102],"in":[109,136,267],"data-driven":[111],"way.":[112],"First,":[113],"automatically":[115],"detect":[116],"further":[121],"analysis,":[122],"domain":[126,139,143,159],"transformation":[127],"algorithm":[128],"that":[129,236],"detects":[130],"transforming":[133],"trajectories":[135],"spatial":[138],"into":[140],"new":[142,158,163,186],"where":[144],"much":[148],"more":[149,265],"apparent":[150],"thus":[153,246],"easier":[154],"detect.":[156],"The":[157],"also":[160,211],"provides":[161,212],"perspective":[164],"understanding":[166],"Second,":[170],"since":[171],"there":[172],"no":[174],"mature":[175],"metrics":[176],"evaluate":[178],"realism,":[182],"evaluation":[187,209],"metric":[188,210],"based":[189],"on":[190,275],"least-effort":[192],"theory,":[193],"evaluates":[195],"physical":[204],"mental":[206],"consumption.":[207],"modeling.":[216],"Third,":[217],"design":[223],"reinforcement":[225],"learning":[226],"model.":[227],"It":[228],"trains":[229],"agents":[230,249],"our":[232,259,281],"proposed":[233],"reward":[234],"function":[235],"models":[237],"intrinsic":[239],"needs":[240],"\"reducing":[242],"effort":[243],"consumption''":[244],"can":[247],"guide":[248],"behave":[251],"realistically":[252],"avoiding":[254],"collisions.":[255],"Extensive":[256],"experiments":[257],"show":[258],"55.9%":[262],"52.5%":[264],"than":[271],"best":[273],"baselines":[274],"two":[276],"real-world":[277],"datasets.":[278],"We":[279],"release":[280],"codes":[282],"at":[283],"https://github.com/tsinghua-fib-lab/TECRL.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}