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...
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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. |
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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&date=20220525&DB=EPODOC&CC=GB&NR=2601202A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220525&DB=EPODOC&CC=GB&NR=2601202A$$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> |
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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 |
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