Adversarial learning of driving behavior

Embodiments described herein disclose methods and systems for adversarial learning in autonomous vehicle path modeling. The systems and methods collect states of the vehicle in the environment to predict a path. The predicted path is compared for variance from an actual path. The variance between th...

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Bibliographische Detailangaben
1. Verfasser:	Olabiyi, Oluwatobi O
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROLLING COUNTING PHYSICS REGULATING SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Beschreibung
Zusammenfassung:	Embodiments described herein disclose methods and systems for adversarial learning in autonomous vehicle path modeling. The systems and methods collect states of the vehicle in the environment to predict a path. The predicted path is compared for variance from an actual path. The variance between the paths, in light of other data, is used to modify the driving models, to create more accurate representations of expert driving in autonomous vehicle path generation.