TURN AWARE MACHINE LEARNING FOR TRAFFIC BEHAVIOR PREDICTION

TURN AWARE MACHINE LEARNING FOR TRAFFIC BEHAVIOR PREDICTION

An autonomous vehicle collects sensor data of an environment surrounding the autonomous vehicle including traffic entities such as pedestrians, bicyclists, or other vehicles. The sensor data is provided to a machine learning based model along with an expected turn direction of the autonomous vehicle...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: HARTMANN, Till S, MAAT, Jacob Reinier, SYLVESTRE, Kevin W, ANTHONY, Samuel English, ROSE, Dylan James
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
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
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Beschreibung
Zusammenfassung:An autonomous vehicle collects sensor data of an environment surrounding the autonomous vehicle including traffic entities such as pedestrians, bicyclists, or other vehicles. The sensor data is provided to a machine learning based model along with an expected turn direction of the autonomous vehicle to determine a hidden context attribute of a traffic entity given the expected turn direction of the autonomous vehicle. The hidden context attribute of the traffic entity represents factors that affect the behavior of the traffic entity, and the hidden context attribute is used to predict future behavior of the traffic entity. Instructions to control the autonomous vehicle are generated based on the hidden context attribute.