Abstract: Systems and methods for training AV models in accordance with embodiments of the invention are illustrated. One embodiment includes an autonomous vehicle (AV), a vehicle, a processor, and a memory, where the memory contains an AV model capable of driving the vehicle without human input, where the AV model is trained on a plurality of edge case scenarios. In a still further additional embodiment, a method for training AV models, including obtaining a data structure storing a plurality of scenarios that an AV can encounter, and distance metrics indicating the distance between each scenario, generating a list of edge case scenarios within the plurality of scenarios, identifying hazard frames within the edge case scenarios, encoding the hazard frames into one or more records interpretable by an AV model, and training the AV model using the one or more records.