{"id":"https://openalex.org/W6906460500","doi":"https://doi.org/10.17169/refubium-34991","title":"Swarm-Based Trajectory Planning for Autonomous Cars","display_name":"Swarm-Based Trajectory Planning for Autonomous Cars","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6906460500","doi":"https://doi.org/10.17169/refubium-34991"},"language":"en","primary_location":{"id":"pmh:oai:aleph.bib-bvb.de:BVB01-033739374","is_oa":false,"landing_page_url":"https://refubium.fu-berlin.de/handle/fub188/35275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"software, multimedia"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.17169/refubium-34991","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ulbrich, Fritz","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ulbrich, Fritz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.6025999784469604,"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":0.6025999784469604,"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":0.13950000703334808,"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":0.04690000042319298,"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/trajectory","display_name":"Trajectory","score":0.6693999767303467},{"id":"https://openalex.org/keywords/flocking","display_name":"Flocking (texture)","score":0.5810999870300293},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5618000030517578},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.5134000182151794},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.507099986076355},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.499099999666214},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.4115999937057495},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.4058000147342682},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4050999879837036}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6693999767303467},{"id":"https://openalex.org/C2781220375","wikidata":"https://www.wikidata.org/wiki/Q814208","display_name":"Flocking (texture)","level":2,"score":0.5810999870300293},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5618000030517578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5156000256538391},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.5134000182151794},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.507099986076355},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.499099999666214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44859999418258667},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4050999879837036},{"id":"https://openalex.org/C181335050","wikidata":"https://www.wikidata.org/wiki/Q14915018","display_name":"Swarm behaviour","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.3531000018119812},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3400999903678894},{"id":"https://openalex.org/C9628104","wikidata":"https://www.wikidata.org/wiki/Q788009","display_name":"Autonomous system (mathematics)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C2986897749","wikidata":"https://www.wikidata.org/wiki/Q231761","display_name":"Potential field","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.296999990940094},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C188048851","wikidata":"https://www.wikidata.org/wiki/Q2298569","display_name":"Road map","level":2,"score":0.2628999948501587}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:aleph.bib-bvb.de:BVB01-033739374","is_oa":false,"landing_page_url":"https://refubium.fu-berlin.de/handle/fub188/35275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"software, multimedia"},{"id":"doi:10.17169/refubium-34991","is_oa":true,"landing_page_url":"https://doi.org/10.17169/refubium-34991","pdf_url":null,"source":{"id":"https://openalex.org/S7407052913","display_name":"Universit\u00e4tsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"thesis"}],"best_oa_location":{"id":"doi:10.17169/refubium-34991","is_oa":true,"landing_page_url":"https://doi.org/10.17169/refubium-34991","pdf_url":null,"source":{"id":"https://openalex.org/S7407052913","display_name":"Universit\u00e4tsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"thesis"},"sustainable_development_goals":[{"score":0.8319504261016846,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,145],"thesis":[1,146],"aims":[2],"to":[3,48,150,161,191,202,248],"enable":[4],"efficient":[5],"trajectory":[6,86,164],"planning":[7,87,124],"for":[8,67,123,207,243,251],"autonomous":[9,52,76,244],"vehicles":[10,61],"without":[11,130],"the":[12,21,32,43,49,57,71,74,108,118,155,171,193,204,236,252],"requirement":[13],"of":[14,20,34,51,59,73,81,111,140,158,180,254],"a":[15,78,102,131,177,198,208,240],"map":[16,96,103,132],"or":[17,99],"prior":[18],"knowledge":[19,139],"environment.":[22],"For":[23],"this":[24,55],"purpose,":[25],"an":[26,148],"approach":[27,149,216],"is":[28,97,104,143,189,200,217,246],"presented,":[29],"which":[30],"adapts":[31],"concept":[33],"trail":[35],"pheromones":[36],"used":[37,63],"by":[38],"ants":[39],"as":[40,42,64],"well":[41],"collective":[44],"animals'":[45],"flocking":[46],"behavior":[47,110,242],"domain":[50],"vehicles.":[53],"In":[54],"way,":[56],"drivers":[58],"surrounding":[60,194],"are":[62,92,174],"additional":[65],"input":[66],"anticipatory":[68],"driving,":[69],"expanding":[70],"capabilities":[72],"individual":[75],"car:":[77],"typical":[79],"achievement":[80],"swarm":[82,241],"intelligence.":[83],"While":[84],"map-based":[85,255],"has":[88],"many":[89],"advantages,":[90],"there":[91],"situations":[93],"when":[94],"no":[95],"available":[98],"localization":[100],"in":[101,127,219,228],"too":[105],"inaccurate.":[106],"Also,":[107],"actual":[109],"road":[112,141],"users":[113],"may":[114],"differ":[115],"significantly":[116],"from":[117],"given":[119],"map.":[120],"Existing":[121],"approaches":[122],"driving":[125],"maneuvers":[126],"urban":[128],"traffic":[129],"decouple":[133],"lateral":[134],"and":[135,170,197,224],"longitudinal":[136],"planning.":[137,165,256],"Usually,":[138],"geometry":[142],"assumed.":[144],"presents":[147],"overcome":[151],"those":[152],"limitations,":[153],"adopting":[154],"established":[156],"theory":[157],"elastic":[159],"bands":[160],"implement":[162],"swarm-based":[163,185],"The":[166,215,231],"vehicle's":[167],"dynamic":[168],"restrictions":[169],"driver's":[172],"preferences":[173],"represented":[175],"with":[176],"comprehensive":[178],"set":[179],"parameterized":[181],"objective":[182],"functions.":[183],"A":[184],"motion":[186],"prediction":[187],"algorithm":[188],"introduced":[190],"predict":[192],"vehicles'":[195],"trajectories,":[196],"heuristic":[199],"presented":[201,237],"choose":[203],"best":[205],"candidate":[206],"leader":[209],"vehicle":[210],"based":[211],"on":[212,221],"weighted":[213],"criteria.":[214],"evaluated":[218],"simulation,":[220],"recorded":[222],"data,":[223],"live":[225],"field":[226],"tests":[227],"real":[229],"traffic.":[230],"experimental":[232],"results":[233],"show":[234],"that":[235],"approach,":[238],"implementing":[239],"cars,":[245],"valid":[247],"temporarily":[249],"compensate":[250],"advantages":[253]},"counts_by_year":[],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
