{"id":"https://openalex.org/W7106025138","doi":"https://doi.org/10.48550/arxiv.2511.12018","title":"Enhancing Road Safety Through Multi-Camera Image Segmentation with Post-Encroachment Time Analysis","display_name":"Enhancing Road Safety Through Multi-Camera Image Segmentation with Post-Encroachment Time Analysis","publication_year":2025,"publication_date":"2025-11-15","ids":{"openalex":"https://openalex.org/W7106025138","doi":"https://doi.org/10.48550/arxiv.2511.12018"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.12018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.12018","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.12018","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chaudhuri, Shounak Ray","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chaudhuri, Shounak Ray","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jahangiri, Arash","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jahangiri, Arash","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Paolini, Christopher","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paolini, Christopher","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.6557000279426575,"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":0.6557000279426575,"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":0.1632000058889389,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.014600000344216824,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/intersection","display_name":"Intersection (aeronautics)","score":0.705299973487854},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5990999937057495},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5440999865531921},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5246000289916992},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5139999985694885},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48330000042915344},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4235000014305115},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4219000041484833},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4189000129699707}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.705299973487854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906999945640564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6313999891281128},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5990999937057495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5547999739646912},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5440999865531921},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5139999985694885},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4235000014305115},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C28751775","wikidata":"https://www.wikidata.org/wiki/Q2112539","display_name":"Homography","level":4,"score":0.39149999618530273},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3529999852180481},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.35100001096725464},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.34880000352859497},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C42629822","wikidata":"https://www.wikidata.org/wiki/Q1346408","display_name":"Geocoding","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3025999963283539},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2824000120162964},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.2671000063419342},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.12018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.12018","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.12018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.12018","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6711918711662292,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"safety":[1,36,198],"analysis":[2,183],"at":[3,44,168],"signalized":[4],"intersections":[5],"is":[6,127],"vital":[7],"for":[8,34,76,133,160,184,192],"reducing":[9],"vehicle":[10,77,80,104,123],"and":[11,23,50,124,152,195],"pedestrian":[12],"collisions,":[13],"yet":[14],"traditional":[15],"crash-based":[16],"studies":[17],"are":[18,82],"limited":[19],"by":[20],"data":[21,126,159],"sparsity":[22],"latency.":[24],"This":[25,174],"paper":[26],"presents":[27],"a":[28,85,189],"novel":[29,99],"multi-camera":[30],"computer":[31],"vision":[32],"framework":[33],"real-time":[35,153],"assessment":[37],"through":[38],"Post-Encroachment":[39],"Time":[40],"(PET)":[41],"computation,":[42],"demonstrated":[43],"the":[45,142,177],"intersection":[46,197],"of":[47,171,179],"H":[48],"Street":[49],"Broadway":[51],"in":[52,129],"Chula":[53],"Vista,":[54],"California.":[55],"Four":[56],"synchronized":[57],"cameras":[58],"provide":[59],"continuous":[60],"visual":[61],"coverage,":[62],"with":[63,149],"each":[64],"frame":[65],"processed":[66],"on":[67,108,155],"NVIDIA":[68],"Jetson":[69],"AGX":[70],"Xavier":[71],"devices":[72],"using":[73,89],"YOLOv11":[74],"segmentation":[75],"detection.":[78],"Detected":[79],"polygons":[81],"transformed":[83],"into":[84],"unified":[86],"bird's-eye":[87],"map":[88],"homography":[90],"matrices,":[91],"enabling":[92],"alignment":[93],"across":[94],"overlapping":[95],"camera":[96],"views.":[97],"A":[98],"pixel-level":[100],"PET":[101,125,182],"algorithm":[102],"measures":[103],"position":[105],"without":[106],"reliance":[107],"fixed":[109],"cells,":[110],"allowing":[111],"fine-grained":[112],"hazard":[113],"visualization":[114],"via":[115],"dynamic":[116],"heatmaps,":[117],"accurate":[118],"to":[119,145],"3.3":[120],"sq-cm.":[121],"Timestamped":[122],"stored":[128],"an":[130,161,169],"SQL":[131],"database":[132],"long-term":[134],"monitoring.":[135],"Results":[136],"over":[137],"various":[138],"time":[139],"intervals":[140],"demonstrate":[141],"framework's":[143],"ability":[144],"identify":[146],"high-risk":[147],"regions":[148],"sub-second":[150],"precision":[151],"throughput":[154],"edge":[156],"devices,":[157],"producing":[158],"800":[162,164],"x":[163],"pixel":[165],"logarithmic":[166],"heatmap":[167],"average":[170],"2.68":[172],"FPS.":[173],"study":[175],"validates":[176],"feasibility":[178],"decentralized":[180],"vision-based":[181],"intelligent":[185],"transportation":[186],"systems,":[187],"offering":[188],"replicable":[190],"methodology":[191],"high-resolution,":[193],"real-time,":[194],"scalable":[196],"evaluation.":[199]},"counts_by_year":[],"updated_date":"2025-11-19T23:39:43.309859","created_date":"2025-11-19T00:00:00"}