GRAPH NEURAL NETWORKS FOR PARSING ROADS

Systems and methods for predicting drivable paths relative to road segments are disclosed. In one implementation, a system includes a processor programmed to access topographical information associated with a road segment; generate a topographical representation of the road segment based on the topo...

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Bibliographische Detailangaben
1. Verfasser:	FERENCZ, Andras
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES CONTROLLING GYROSCOPIC INSTRUMENTS MEASURING MEASURING DISTANCES, LEVELS OR BEARINGS NAVIGATION PERFORMING OPERATIONS PHOTOGRAMMETRY OR VIDEOGRAMMETRY PHYSICS REGULATING ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT SURVEYING SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES TESTING TRANSPORTING VEHICLES IN GENERAL
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Beschreibung
Zusammenfassung:	Systems and methods for predicting drivable paths relative to road segments are disclosed. In one implementation, a system includes a processor programmed to access topographical information associated with a road segment; generate a topographical representation of the road segment based on the topographical information; input the topographical representation of the road segment to a trained model, wherein the trained model includes a graph neural network and is configured to predict at least one drivable path relative to the road segment based on the topographical representation of the road segment; receive, from the trained model, information identifying the drivable path; and store the information identifying the drivable path in a map.