PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle...
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Ding, Kai Parasuram, Aishwarya Sagar, Anoosha Liu, Xin Saxena, Alisha Ross, Stéphane |
| description | Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2023139578A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2023139578A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2023139578A13</originalsourceid><addsrcrecordid>eNqNyrEKwjAUBdAuDqL-wwNnwTaIdQzP2yZFU0meBadSJE6ihfr_mMEPcDrLmWfNxeNoWayrSddwQuJ1A5bWWwSyjsSAUgpwDGor0il3IJzh0-cbdTCWTwjLbPYYnlNc_Vxk6wrCZhPHdx-ncbjHV_z011BsC5Wrw25f6lz9t74MZC5M</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES</title><source>esp@cenet</source><creator>Ding, Kai ; Parasuram, Aishwarya ; Sagar, Anoosha ; Liu, Xin ; Saxena, Alisha ; Ross, Stéphane</creator><creatorcontrib>Ding, Kai ; Parasuram, Aishwarya ; Sagar, Anoosha ; Liu, Xin ; Saxena, Alisha ; Ross, Stéphane</creatorcontrib><description>Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION ; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES ; COUNTING ; PERFORMING OPERATIONS ; PHYSICS ; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT ; TRANSPORTING ; VEHICLES IN GENERAL</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230504&DB=EPODOC&CC=US&NR=2023139578A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230504&DB=EPODOC&CC=US&NR=2023139578A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Ding, Kai</creatorcontrib><creatorcontrib>Parasuram, Aishwarya</creatorcontrib><creatorcontrib>Sagar, Anoosha</creatorcontrib><creatorcontrib>Liu, Xin</creatorcontrib><creatorcontrib>Saxena, Alisha</creatorcontrib><creatorcontrib>Ross, Stéphane</creatorcontrib><title>PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES</title><description>Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</subject><subject>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</subject><subject>COUNTING</subject><subject>PERFORMING OPERATIONS</subject><subject>PHYSICS</subject><subject>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</subject><subject>TRANSPORTING</subject><subject>VEHICLES IN GENERAL</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrEKwjAUBdAuDqL-wwNnwTaIdQzP2yZFU0meBadSJE6ihfr_mMEPcDrLmWfNxeNoWayrSddwQuJ1A5bWWwSyjsSAUgpwDGor0il3IJzh0-cbdTCWTwjLbPYYnlNc_Vxk6wrCZhPHdx-ncbjHV_z011BsC5Wrw25f6lz9t74MZC5M</recordid><startdate>20230504</startdate><enddate>20230504</enddate><creator>Ding, Kai</creator><creator>Parasuram, Aishwarya</creator><creator>Sagar, Anoosha</creator><creator>Liu, Xin</creator><creator>Saxena, Alisha</creator><creator>Ross, Stéphane</creator><scope>EVB</scope></search><sort><creationdate>20230504</creationdate><title>PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES</title><author>Ding, Kai ; Parasuram, Aishwarya ; Sagar, Anoosha ; Liu, Xin ; Saxena, Alisha ; Ross, Stéphane</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2023139578A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</topic><topic>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</topic><topic>COUNTING</topic><topic>PERFORMING OPERATIONS</topic><topic>PHYSICS</topic><topic>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</topic><topic>TRANSPORTING</topic><topic>VEHICLES IN GENERAL</topic><toplevel>online_resources</toplevel><creatorcontrib>Ding, Kai</creatorcontrib><creatorcontrib>Parasuram, Aishwarya</creatorcontrib><creatorcontrib>Sagar, Anoosha</creatorcontrib><creatorcontrib>Liu, Xin</creatorcontrib><creatorcontrib>Saxena, Alisha</creatorcontrib><creatorcontrib>Ross, Stéphane</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ding, Kai</au><au>Parasuram, Aishwarya</au><au>Sagar, Anoosha</au><au>Liu, Xin</au><au>Saxena, Alisha</au><au>Ross, Stéphane</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES</title><date>2023-05-04</date><risdate>2023</risdate><abstract>Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US2023139578A1 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES COUNTING PERFORMING OPERATIONS PHYSICS ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT TRANSPORTING VEHICLES IN GENERAL |
| title | PREDICTING AGENT TRAJECTORIES IN THE PRESENCE OF ACTIVE EMERGENCY VEHICLES |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T09%3A59%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Ding,%20Kai&rft.date=2023-05-04&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2023139578A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |