{"id":"https://openalex.org/W3017369632","doi":"https://doi.org/10.1109/access.2020.2987777","title":"Predicting Pedestrian Intention to Cross the Road","display_name":"Predicting Pedestrian Intention to Cross the Road","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3017369632","doi":"https://doi.org/10.1109/access.2020.2987777","mag":"3017369632"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2987777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2987777","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09064816.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09064816.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086601176","display_name":"Karam Abughalieh","orcid":null},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karam M. Abughalieh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Oakland University, Rochester, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Oakland University, Rochester, USA","institution_ids":["https://openalex.org/I177721651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005486222","display_name":"Shadi Alawneh","orcid":"https://orcid.org/0000-0002-3360-9440"},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shadi G. Alawneh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Oakland University, Rochester, USA"],"raw_orcid":"https://orcid.org/0000-0002-3360-9440","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Oakland University, Rochester, USA","institution_ids":["https://openalex.org/I177721651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177721651"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.5773,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.89131659,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"72558","last_page":"72569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9979000091552734,"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":0.9336166977882385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7509207129478455},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6764045357704163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6105124354362488},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5979676246643066},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5766472220420837},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5143426656723022},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49394160509109497},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.34985458850860596},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11354479193687439},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06240835785865784}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.9336166977882385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7509207129478455},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6764045357704163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6105124354362488},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5979676246643066},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5766472220420837},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5143426656723022},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49394160509109497},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.34985458850860596},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11354479193687439},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06240835785865784},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2987777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2987777","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09064816.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0dc8b468fa3541a3a34f0c58799ee143","is_oa":true,"landing_page_url":"https://doaj.org/article/0dc8b468fa3541a3a34f0c58799ee143","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 72558-72569 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2987777","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2987777","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09064816.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7200000286102295,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3017369632.pdf","grobid_xml":"https://content.openalex.org/works/W3017369632.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W626667024","https://openalex.org/W1579387951","https://openalex.org/W1584874746","https://openalex.org/W1861492603","https://openalex.org/W1906654320","https://openalex.org/W1937999893","https://openalex.org/W2044271997","https://openalex.org/W2048960138","https://openalex.org/W2054911734","https://openalex.org/W2078238240","https://openalex.org/W2079418687","https://openalex.org/W2101415982","https://openalex.org/W2102605133","https://openalex.org/W2111025459","https://openalex.org/W2130306091","https://openalex.org/W2150893603","https://openalex.org/W2154889144","https://openalex.org/W2344839403","https://openalex.org/W2519833594","https://openalex.org/W2570343428","https://openalex.org/W2583585015","https://openalex.org/W2586073474","https://openalex.org/W2743406267","https://openalex.org/W2814153150","https://openalex.org/W2883770893","https://openalex.org/W2903584792","https://openalex.org/W2909273520","https://openalex.org/W2932069590","https://openalex.org/W2962730651","https://openalex.org/W2963037989","https://openalex.org/W3003846480","https://openalex.org/W3106250896","https://openalex.org/W3109360409","https://openalex.org/W4293584584","https://openalex.org/W6604387964","https://openalex.org/W6639102338","https://openalex.org/W6726868649","https://openalex.org/W6733290759","https://openalex.org/W6750227808","https://openalex.org/W6756633688","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W566791342","https://openalex.org/W3136214354","https://openalex.org/W3172487415","https://openalex.org/W608736979","https://openalex.org/W631954924","https://openalex.org/W2148933895"],"abstract_inverted_index":{"The":[0,35,77,128],"goal":[1],"of":[2,8,37,45],"this":[3],"research":[4],"is":[5,22,40,120,131],"the":[6,16,33,43,49,52,69,75,80,89,97,113,118,126],"development":[7],"a":[9,20,24,56,100,123],"driver":[10,17],"assistant":[11],"feature,":[12],"which":[13],"can":[14],"warn":[15],"in":[18,23,85,112,139],"case":[19],"pedestrian":[21,39,46,70,108,114,138],"potential":[25],"risk":[26],"due":[27],"to":[28,31,67,95,122],"sudden":[29],"intention":[30],"cross":[32],"road.":[34,53],"process":[36],"crossing":[38],"defined":[41],"as":[42],"changing":[44],"orientation":[47,71],"on":[48],"curb":[50],"toward":[51,117],"We":[54],"built":[55],"Convolutional":[57],"Neural":[58],"Network":[59],"(CNN)":[60],"model":[61,78,130],"combined":[62],"with":[63],"depth":[64,90],"sensing":[65],"camera":[66],"estimate":[68],"and":[72,109,142],"distance":[73],"from":[74],"vehicle.":[76],"detects":[79],"higher":[81],"human":[82],"body":[83],"keypoints":[84],"2D":[86],"space":[87],"while":[88],"info":[91,104],"make":[92],"it":[93],"possible":[94],"translate":[96],"points":[98],"into":[99],"3D":[101],"space.":[102],"These":[103],"are":[105],"tracked":[106],"per":[107],"any":[110],"change":[111],"moving":[115],"pattern":[116],"road":[119],"translated":[121],"warning":[124],"for":[125],"driver.":[127],"CNN":[129],"end-end":[132],"trained":[133],"using":[134],"different":[135,140],"datasets":[136],"presenting":[137],"configurations":[141],"scenes.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}