{"id":"https://openalex.org/W2892083523","doi":"https://doi.org/10.1109/icarcv.2018.8581368","title":"Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data","display_name":"Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2892083523","doi":"https://doi.org/10.1109/icarcv.2018.8581368","mag":"2892083523"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv.2018.8581368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2018.8581368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.06045","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007270816","display_name":"Pavan Vasishta","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pavan Vasishta","raw_affiliation_strings":["Inria, Univ. Grenoble Alpes, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I4210101348","https://openalex.org/I899635006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077485006","display_name":"Dominique Vaufreydaz","orcid":"https://orcid.org/0000-0002-8825-0973"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Dominique Vaufreydaz","raw_affiliation_strings":["CNRS, Univ. Grenoble Alpes, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS, Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I899635006","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070587077","display_name":"Anne Spalanzani","orcid":"https://orcid.org/0000-0003-4813-4940"},"institutions":[{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Anne Spalanzani","raw_affiliation_strings":["Inria, Univ. Grenoble Alpes, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I4210101348","https://openalex.org/I899635006"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9766,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76090418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"247","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9976000189781189,"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":0.9976000189781189,"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/T10370","display_name":"Traffic and Road Safety","score":0.994700014591217,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7772095203399658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6517707705497742},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4903864860534668},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.49037694931030273},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4642983078956604},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.44479650259017944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37476658821105957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3405492305755615},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.21218866109848022},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14358747005462646},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1347028613090515},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10515838861465454}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7772095203399658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6517707705497742},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4903864860534668},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.49037694931030273},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4642983078956604},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.44479650259017944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37476658821105957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3405492305755615},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.21218866109848022},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14358747005462646},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1347028613090515},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10515838861465454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icarcv.2018.8581368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2018.8581368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1809.06045","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.06045","pdf_url":"https://arxiv.org/pdf/1809.06045","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.06045","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.06045","pdf_url":"https://arxiv.org/pdf/1809.06045","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G5172574513","display_name":"Automatic redistribution of a fleet of car-sharing vehicles and parking valet","funder_award_id":"ANR-15-CE22-0013","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G8390333486","display_name":null,"funder_award_id":"ANR-15-CE22-0013-02","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2892083523.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W42560795","https://openalex.org/W1933657216","https://openalex.org/W1964806982","https://openalex.org/W1979973762","https://openalex.org/W2024479254","https://openalex.org/W2031101993","https://openalex.org/W2100675387","https://openalex.org/W2101821104","https://openalex.org/W2146183743","https://openalex.org/W2146948159","https://openalex.org/W2152891050","https://openalex.org/W2167052694","https://openalex.org/W2567948266","https://openalex.org/W2570343428","https://openalex.org/W2603203130","https://openalex.org/W2742283667","https://openalex.org/W2911273949","https://openalex.org/W6740017579"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2084326697","https://openalex.org/W2194396582","https://openalex.org/W2027903142","https://openalex.org/W2082284720","https://openalex.org/W2116722627"],"abstract_inverted_index":{"Autonomous":[0],"Vehicles":[1],"navigating":[2],"in":[3,43,180],"urban":[4],"areas":[5],"have":[6],"a":[7,109,123,163],"need":[8,62],"to":[9,33,74,84,116,127],"understand":[10],"and":[11,29,102,139,151],"predict":[12,117],"future":[13,35],"pedestrian":[14,27,118],"behavior":[15,28,141],"for":[16,63,66],"safer":[17],"navigation.":[18],"This":[19,90],"high":[20],"level":[21],"of":[22,52,57,87,105,130,142,166],"situational":[23],"awareness":[24],"requires":[25],"observing":[26],"extrapolating":[30],"their":[31],"positions":[32,119],"know":[34],"positions.":[36],"While":[37],"some":[38,86],"work":[39,97],"has":[40],"been":[41],"done":[42],"this":[44,70],"field":[45],"using":[46,98],"Hidden":[47,77],"Markov":[48,78],"Models":[49],"(HMMs),":[50],"one":[51],"the":[53,58,61,75,103,111,128,131,146,167,174],"few":[54],"observed":[55,172],"drawbacks":[56],"method":[59,81,134,176],"is":[60,82,91,114,135,160,171,177],"informed":[64],"priors":[65],"learning":[67],"behavior.":[68],"In":[69],"work,":[71],"an":[72],"extension":[73],"Growing":[76],"Model":[79],"(GHMM)":[80],"proposed":[83,112,175],"solve":[85],"these":[88],"drawbacks.":[89],"achieved":[92],"by":[93],"building":[94],"on":[95],"existing":[96],"potential":[99],"cost":[100],"maps":[101],"principle":[104],"Natural":[106],"Vision.":[107],"As":[108],"consequence,":[110],"model":[113,147],"able":[115],"more":[120],"precisely":[121],"over":[122,137],"longer":[124],"horizon":[125],"compared":[126,161],"state":[129,165],"art.":[132],"The":[133,154],"tested":[136],"\u201clegal\u201d":[138],"\u201cillegal\u201d":[140],"pedestrians,":[143],"having":[144],"trained":[145,164],"with":[148,156],"sparse":[149],"observations":[150],"partial":[152],"trajectories.":[153],"method,":[155],"no":[157],"training":[158],"data,":[159],"against":[162],"art":[168],"model.":[169],"It":[170],"that":[173],"robust":[178],"even":[179],"new,":[181],"previously":[182],"unseen":[183],"areas.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
