{"id":"https://openalex.org/W4406524045","doi":"https://doi.org/10.1109/tits.2024.3522971","title":"An Efficient Deep Spatio-Temporal Context Aware Decision Network (DST-CAN) for Predictive Manoeuvre Planning on Highways","display_name":"An Efficient Deep Spatio-Temporal Context Aware Decision Network (DST-CAN) for Predictive Manoeuvre Planning on Highways","publication_year":2025,"publication_date":"2025-01-17","ids":{"openalex":"https://openalex.org/W4406524045","doi":"https://doi.org/10.1109/tits.2024.3522971"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3522971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3522971","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017692956","display_name":"Jayabrata Chowdhury","orcid":"https://orcid.org/0000-0003-1534-6066"},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jayabrata Chowdhury","raw_affiliation_strings":["Robert Bosch Centre for Cyber-Physical Systems, Indian Institute of Science, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Robert Bosch Centre for Cyber-Physical Systems, Indian Institute of Science, Bengaluru, India","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765440","display_name":"Suresh Sundaram","orcid":"https://orcid.org/0000-0001-6275-0921"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suresh Sundaram","raw_affiliation_strings":["Department of Aerospace Engineering, Artificial Intelligence and Robotics Laboratory, Indian Institute of Science, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Artificial Intelligence and Robotics Laboratory, Indian Institute of Science, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014416757","display_name":"N.D. Rao","orcid":"https://orcid.org/0000-0001-7570-1897"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nishanth Rao","raw_affiliation_strings":["Department of Aerospace Engineering, Artificial Intelligence and Robotics Laboratory, Indian Institute of Science, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Artificial Intelligence and Robotics Laboratory, Indian Institute of Science, Bengaluru, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080692534","display_name":"N. Sundararajan","orcid":"https://orcid.org/0000-0002-6972-8775"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Narasimman Sundararajan","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017692956"],"corresponding_institution_ids":["https://openalex.org/I4210151956"],"apc_list":null,"apc_paid":null,"fwci":2.0755,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.83087174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"26","issue":"3","first_page":"2944","last_page":"2954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9575999975204468,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9575999975204468,"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"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9438999891281128,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9373999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/context","display_name":"Context (archaeology)","score":0.625646710395813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.550696074962616},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.4525423049926758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39566949009895325},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.22656115889549255}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.625646710395813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.550696074962616},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.4525423049926758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39566949009895325},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.22656115889549255},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3522971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3522971","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1978150223","https://openalex.org/W2146972303","https://openalex.org/W2424778531","https://openalex.org/W2580495915","https://openalex.org/W2741066535","https://openalex.org/W2784715585","https://openalex.org/W2791814097","https://openalex.org/W2798786289","https://openalex.org/W2803184913","https://openalex.org/W2940129212","https://openalex.org/W2953920664","https://openalex.org/W2963309363","https://openalex.org/W2963906196","https://openalex.org/W2963914175","https://openalex.org/W2971306974","https://openalex.org/W2975767248","https://openalex.org/W2983227562","https://openalex.org/W2989851631","https://openalex.org/W3034263760","https://openalex.org/W3090166818","https://openalex.org/W3128196514","https://openalex.org/W3132231991","https://openalex.org/W3165538189","https://openalex.org/W3193512724","https://openalex.org/W3196204376","https://openalex.org/W3200533894","https://openalex.org/W3202129464","https://openalex.org/W4212796772","https://openalex.org/W4285173565","https://openalex.org/W4285272860","https://openalex.org/W4285307478","https://openalex.org/W4292347911","https://openalex.org/W4385517014"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0,192,210,258],"safety":[1],"and":[2,34,68,91,115,125,132,150,187,244],"efficiency":[3],"of":[4,17,84,138,194,239,242],"an":[5,21,228],"Autonomous":[6],"Vehicle":[7],"(AV)":[8],"manoeuvre":[9,36,52,70,117,134,208],"planning":[10],"heavily":[11],"depend":[12],"on":[13,56],"the":[14,81,195,201,215,222,237,250],"future":[15,28,82],"trajectories":[16,83],"surrounding":[18,26,86],"vehicles.":[19,87],"If":[20],"AV":[22],"can":[23,31],"predict":[24,80,221],"its":[25,85],"vehicles\u2019":[27],"trajectories,":[29,94],"it":[30],"make":[32],"safe":[33,114],"efficient":[35,116],"decisions.":[37,135,170,191],"In":[38],"this":[39],"paper,":[40],"we":[41],"present":[42],"a":[43,75,95,109,113,245,262],"Deep":[44],"Spatio-Temporal":[45],"Context-Aware":[46],"decision":[47,110,223],"Network":[48],"(DST-CAN)":[49],"for":[50,54,163,207],"predictive":[51,69],"decisions":[53,71,182],"AVs":[55],"highways.":[57],"DST-CAN":[58,73,139,172,196,219],"has":[59,140,231],"two":[60,126,145],"main":[61],"components,":[62],"namely":[63],"spatio-temporal":[64,96],"context-aware":[65,97,104,216,259],"map":[66,100,260],"generator":[67],"engine.":[72],"employ":[74],"memory":[76],"neuron":[77],"network":[78,129],"to":[79,108,159,168,220,235,248],"Using":[88],"look-ahead":[89],"prediction":[90,240,265],"past":[92],"actual":[93,184,255],"probability":[98],"occupancy":[99],"is":[101,157,267],"generated.":[102],"These":[103],"maps":[105,217],"as":[106],"input":[107],"engine":[111],"generate":[112,160],"decision.":[118],"Here,":[119],"CNN":[120],"helps":[121],"extract":[122],"feature":[123],"space,":[124],"fully":[127],"connected":[128],"generates":[130],"longitudinal":[131],"lateral":[133],"Performance":[136],"evaluation":[137],"been":[141,232],"carried":[142,233],"out":[143,234],"using":[144,176],"publicly":[146],"available":[147],"NGSIM":[148],"US-101":[149],"I-80":[151],"highway":[152],"datasets.":[153],"A":[154],"traffic":[155,185,256],"rule":[156],"defined":[158],"ground":[161,189],"truths":[162],"these":[164],"datasets":[165],"in":[166],"addition":[167],"human":[169,180],"Two":[171],"models":[173,197,206],"are":[174,198],"trained":[175],"imitation":[177],"learning":[178],"with":[179,200,261],"driving":[181],"from":[183],"data":[186],"rule-based":[188],"truth":[190],"performances":[193],"compared":[199],"state-of-the-art":[202],"Convolutional":[203],"Social-LSTM":[204],"(CS-LSTM)":[205],"prediction.":[209],"results":[211],"clearly":[212],"indicate":[213],"that":[214],"help":[218],"accurately":[224],"over":[225,254],"CS-LSTM.":[226],"Further,":[227],"ablation":[229],"study":[230,247],"understand":[236,249],"effect":[238],"horizons":[241],"performance":[243],"robustness":[246],"near":[251,270],"collision":[252],"scenarios":[253],"observations.":[257],"3":[263],"second":[264],"horizon":[266],"robust":[268],"against":[269],"collision.":[271]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
