Trajectory generation using road network model

A method and system of trajectory generation using a road network model comprising; obtaining, using at least one processor of a vehicle, a location of the vehicle, sensor data collected at the location; obtaining and map data for the location (701). Generating, using one or more processors, at leas...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Eric Wolff, Robert Beaudoin
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 Eric Wolff
Robert Beaudoin
description A method and system of trajectory generation using a road network model comprising; obtaining, using at least one processor of a vehicle, a location of the vehicle, sensor data collected at the location; obtaining and map data for the location (701). Generating, using one or more processors, at least one possible trajectory for at least one object at the location, wherein the possible trajectory is constrained in accordance with the map data (702). Predicting, using a machine learning model, a score for the at least one trajectory (703). The system may generate feature vectors generated from an image embedding of the sensor data and the map data. Point clouds may be utilised in conjunction with LiDAR.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_GB2601202A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>GB2601202A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_GB2601202A3</originalsourceid><addsrcrecordid>eNrjZNALKUrMSk0uyS-qVEhPzUstSizJzM9TKC3OzEtXKMpPTFHISy0pzy_KVsjNT0nN4WFgTUvMKU7lhdLcDPJuriHOHrqpBfnxqcUFiclAM0ri3Z2MzAwMjQyMHI0JqwAAgb0p9Q</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Trajectory generation using road network model</title><source>esp@cenet</source><creator>Eric Wolff ; Robert Beaudoin</creator><creatorcontrib>Eric Wolff ; Robert Beaudoin</creatorcontrib><description>A method and system of trajectory generation using a road network model comprising; obtaining, using at least one processor of a vehicle, a location of the vehicle, sensor data collected at the location; obtaining and map data for the location (701). Generating, using one or more processors, at least one possible trajectory for at least one object at the location, wherein the possible trajectory is constrained in accordance with the map data (702). Predicting, using a machine learning model, a score for the at least one trajectory (703). The system may generate feature vectors generated from an image embedding of the sensor data and the map data. Point clouds may be utilised in conjunction with LiDAR.</description><language>eng</language><subject>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION ; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES ; CONTROLLING ; PERFORMING OPERATIONS ; PHYSICS ; REGULATING ; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT ; SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES ; TRANSPORTING ; VEHICLES IN GENERAL</subject><creationdate>2022</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&amp;date=20220525&amp;DB=EPODOC&amp;CC=GB&amp;NR=2601202A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20220525&amp;DB=EPODOC&amp;CC=GB&amp;NR=2601202A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Eric Wolff</creatorcontrib><creatorcontrib>Robert Beaudoin</creatorcontrib><title>Trajectory generation using road network model</title><description>A method and system of trajectory generation using a road network model comprising; obtaining, using at least one processor of a vehicle, a location of the vehicle, sensor data collected at the location; obtaining and map data for the location (701). Generating, using one or more processors, at least one possible trajectory for at least one object at the location, wherein the possible trajectory is constrained in accordance with the map data (702). Predicting, using a machine learning model, a score for the at least one trajectory (703). The system may generate feature vectors generated from an image embedding of the sensor data and the map data. Point clouds may be utilised in conjunction with LiDAR.</description><subject>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</subject><subject>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</subject><subject>CONTROLLING</subject><subject>PERFORMING OPERATIONS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><subject>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</subject><subject>SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES</subject><subject>TRANSPORTING</subject><subject>VEHICLES IN GENERAL</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNALKUrMSk0uyS-qVEhPzUstSizJzM9TKC3OzEtXKMpPTFHISy0pzy_KVsjNT0nN4WFgTUvMKU7lhdLcDPJuriHOHrqpBfnxqcUFiclAM0ri3Z2MzAwMjQyMHI0JqwAAgb0p9Q</recordid><startdate>20220525</startdate><enddate>20220525</enddate><creator>Eric Wolff</creator><creator>Robert Beaudoin</creator><scope>EVB</scope></search><sort><creationdate>20220525</creationdate><title>Trajectory generation using road network model</title><author>Eric Wolff ; Robert Beaudoin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_GB2601202A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</topic><topic>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</topic><topic>CONTROLLING</topic><topic>PERFORMING OPERATIONS</topic><topic>PHYSICS</topic><topic>REGULATING</topic><topic>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</topic><topic>SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES</topic><topic>TRANSPORTING</topic><topic>VEHICLES IN GENERAL</topic><toplevel>online_resources</toplevel><creatorcontrib>Eric Wolff</creatorcontrib><creatorcontrib>Robert Beaudoin</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Eric Wolff</au><au>Robert Beaudoin</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Trajectory generation using road network model</title><date>2022-05-25</date><risdate>2022</risdate><abstract>A method and system of trajectory generation using a road network model comprising; obtaining, using at least one processor of a vehicle, a location of the vehicle, sensor data collected at the location; obtaining and map data for the location (701). Generating, using one or more processors, at least one possible trajectory for at least one object at the location, wherein the possible trajectory is constrained in accordance with the map data (702). Predicting, using a machine learning model, a score for the at least one trajectory (703). The system may generate feature vectors generated from an image embedding of the sensor data and the map data. Point clouds may be utilised in conjunction with LiDAR.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_GB2601202A
source esp@cenet
subjects CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION
CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES
CONTROLLING
PERFORMING OPERATIONS
PHYSICS
REGULATING
ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
TRANSPORTING
VEHICLES IN GENERAL
title Trajectory generation using road network model
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T01%3A21%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=Eric%20Wolff&rft.date=2022-05-25&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EGB2601202A%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