Probabilistic neural network for predicting hidden context of traffic entities for autonomous vehicles
Abstract:
An autonomous vehicle uses probabilistic neural networks to predict hidden context attributes associated with traffic entities. The hidden context represents behavior of the traffic entities in the traffic. The probabilistic neural network is configured to receive an image of traffic as input and generate output representing hidden context for a traffic entity displayed in the image. The system executes the probabilistic neural network to generate output representing hidden context for traffic entities encountered while navigating through traffic. The system determines a measure of uncertainty for the output values. The autonomous vehicle uses the measure of uncertainty generated by the probabilistic neural network during navigation.
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