{"id":"https://openalex.org/W4405384342","doi":"https://doi.org/10.1145/3697355.3697391","title":"Research on Intelligent Traffic Dynamic Path Planning Algorithm Based on ArcGIS","display_name":"Research on Intelligent Traffic Dynamic Path Planning Algorithm Based on ArcGIS","publication_year":2024,"publication_date":"2024-09-14","ids":{"openalex":"https://openalex.org/W4405384342","doi":"https://doi.org/10.1145/3697355.3697391"},"language":"en","primary_location":{"id":"doi:10.1145/3697355.3697391","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3697355.3697391","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3697355.3697391?download=true","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Big Data and Internet of Things","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3697355.3697391?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102124062","display_name":"Jia Chen","orcid":"https://orcid.org/0000-0001-8774-9839"},"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":"Jia Chen","raw_affiliation_strings":["Institute of Transportation Engineering, Tsinghua University, Beijing, China and China Communications Asset Management Co.,Ltd, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8774-9839","affiliations":[{"raw_affiliation_string":"Institute of Transportation Engineering, Tsinghua University, Beijing, China and China Communications Asset Management Co.,Ltd, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004196013","display_name":"F. F. Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feizhou Zhang","raw_affiliation_strings":["Institute of Remote Sensing & GIS, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-8566-1155","affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089683375","display_name":"Jing Shi","orcid":"https://orcid.org/0000-0001-6329-0277"},"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":"Jing Shi","raw_affiliation_strings":["Institute of Transportation Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6329-0277","affiliations":[{"raw_affiliation_string":"Institute of Transportation Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongyan Lv","orcid":"https://orcid.org/0009-0009-0430-8057"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Lv","raw_affiliation_strings":["Guangzhou Guojiao Runwan Transportation Information Co., Ltd, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0009-0430-8057","affiliations":[{"raw_affiliation_string":"Guangzhou Guojiao Runwan Transportation Information Co., Ltd, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210113138"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3506977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"221","last_page":"225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14270","display_name":"Simulation and Modeling Applications","score":0.9782000184059143,"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/T14270","display_name":"Simulation and Modeling Applications","score":0.9782000184059143,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9595000147819519,"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/T11106","display_name":"Data Management and Algorithms","score":0.9423999786376953,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7687491178512573},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5983614921569824},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4364496171474457},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.41501808166503906},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3939548134803772},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3892347514629364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2655380964279175},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.22223100066184998},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.14638668298721313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1141679584980011}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7687491178512573},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5983614921569824},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4364496171474457},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.41501808166503906},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3939548134803772},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3892347514629364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2655380964279175},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.22223100066184998},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.14638668298721313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1141679584980011},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3697355.3697391","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3697355.3697391","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3697355.3697391?download=true","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Big Data and Internet of Things","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3697355.3697391","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3697355.3697391","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3697355.3697391?download=true","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Big Data and Internet of Things","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405384342.pdf","grobid_xml":"https://content.openalex.org/works/W4405384342.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2061159212"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W4289260319","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":{"The":[0],"purpose":[1],"of":[2,40,129,150,157],"path":[3,11,41,51,88,113,146],"planning":[4,42,89,114,147],"algorithms":[5,36,90],"is":[6,149],"to":[7,84],"study":[8],"the":[9,38,70,75,81,108,133,144,155,163],"shortest":[10],"between":[12],"two":[13],"points":[14],"in":[15],"a":[16,123],"topological":[17],"network.Many":[18],"scholars":[19],"at":[20],"domestic":[21],"and":[22,31,58,73,101,138,161],"overseas":[23],"have":[24],"conducted":[25],"in-depth":[26],"research":[27],"on":[28,48,117],"this":[29],"topic,":[30],"there":[32],"are":[33],"many":[34],"mature":[35],"available.However,":[37],"application":[39],"in-vehicle":[43],"navigation":[44],"systems":[45],"often":[46],"focuses":[47],"classical":[49,87],"static":[50],"planning,":[52],"which":[53],"cannot":[54],"cope":[55],"with":[56,122],"large-scale":[57],"dynamically":[59],"changing":[60],"traffic":[61,77,119,167],"networks.This":[62],"paper":[63],"takes":[64],"Geographic":[65],"Information":[66],"Systems":[67],"(GIS)":[68],"as":[69,80,92],"starting":[71],"point":[72],"uses":[74],"ArcGIS":[76,145],"network":[78,159],"model":[79],"theoretical":[82],"basis":[83],"implement":[85],"various":[86],"such":[91],"PSP,":[93],"Dijkstra,":[94,99],"DBFS,":[95],"L-dequeue,":[96],"L-2queue,":[97],"improved":[98],"A*,":[100],"A*":[102,134],"bidirectional":[103,135],"search.Experimental":[104],"results":[105,115],"show":[106],"that":[107],"algorithm":[109,137],"can":[110],"provide":[111],"dynamic":[112],"based":[116],"realtime":[118],"flow":[120],"changes,":[121],"running":[124],"speed":[125],"nearly":[126,139],"an":[127],"order":[128],"magnitude":[130],"faster":[131,142],"than":[132,143],"search":[136],"five":[140],"times":[141],"algorithm.This":[148],"great":[151],"significance":[152],"for":[153],"optimizing":[154],"allocation":[156],"road":[158],"resources":[160],"solving":[162],"increasingly":[164],"serious":[165],"urban":[166],"problems.":[168]},"counts_by_year":[],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}