A method of implementing distributed AI or ML learning for autonomous vehicles is disclosed. An AI or ML model specific to a location or a type of the location is generated at a vehicle. In response to a detection that the vehicle is within a proximity to a road side unit (RSU) associated with the location or the type of the location or the vehicle is within a proximity to an additional vehicle that is present or anticipated to be present at the location or the type of the location, causing an AI or ML model transmission to the additional vehicle or the RSU. Based on the causing the AI or ML model reception, causing deployment of an additional AI or ML model in the vehicle to optimize the vehicle for the location or the type of the location.
DISTRIBUTED LEARNING TO LEARN CONTEXT-SPECIFIC DRIVING PATTERNS
VERTEILTES LERNEN ZUM ERLERNEN KONTEXTSPEZIFISCHER FAHRMUSTER
APPRENTISSAGE DISTRIBUÉ POUR APPRENDRE DES MODES DE CONDUITE SPÉCIFIQUES AU CONTEXTE
2022-06-29
Patent
Electronic Resource
English
DISTRIBUTED LEARNING TO LEARN CONTEXT-SPECIFIC DRIVING PATTERNS
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