US 11467579

Here's a concise summary of US Patent 11467579:

Title: Probabilistic neural network for predicting hidden context of traffic entities for autonomous vehicles

Assignee: Perceptive Automata LLC (originally Perceptive Automata Inc)

Inventors: Jacob Reinier Maat, Samuel English Anthony

Filing Date: 2020-02-06

Issue Date: 2022-10-11

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.

Plain-language Overview of Independent Claims:

• Claim 1: This claim describes a computer-implemented method for an autonomous vehicle. The method involves receiving sensor data, identifying a traffic entity, and using a probabilistic neural network to predict the traffic entity's "hidden context" (like their intent or awareness) and a measure of uncertainty for that prediction. Based on these predictions and the uncertainty, the autonomous vehicle then adjusts its navigation, for example, by maintaining a threshold distance from the traffic entity, where this distance is influenced by the uncertainty.
• Claim 10: This claim is similar to Claim 1 but is directed to a system. It includes a processor and memory configured to perform the steps of receiving sensor data, identifying a traffic entity, determining its motion parameters, predicting hidden context and a measure of uncertainty using a probabilistic neural network, and navigating the autonomous vehicle based on these predictions.
• Claim 18: This claim is directed to a non-transitory computer-readable storage medium. This medium stores instructions that, when executed by a processor, cause a computer to perform the same method steps as described in Claim 1, including receiving sensor data, identifying a traffic entity, determining its motion, predicting hidden context and uncertainty via a probabilistic neural network, and navigating the autonomous vehicle accordingly.

Litigation Information:
As of April 26, 2026, the patent is involved in several legal actions:

• A PTAB case, IPR2025-01576, was filed and is currently pending and instituted.
• US cases have been filed in the Texas Western District Court (case 7:25-cv-00594) and the Texas Eastern District Court (case 2:25-cv-00742).
• First worldwide family litigation was filed.
  There are no specific CAFC 2026 dockets found for patent 11467579 in the provided information or from external searches. The existing litigation mentions PTAB and District Courts, not the Court of Appeals for the Federal Circuit.