Described herein relates to a system and method for autonomous vehicle navigation. The technique may combine a Hybrid Predictive Network (HPN) and a Value Function Network (VFN), along with a safety prioritizer, to enhance decision-making and safety. The HPN, built on a symmetric encoder-decoder architecture, may utilize a series of observations to predict future scenarios. The VFN may also estimate state-action value functions, combining HPN's predictive capabilities with decision-making, improving navigation. A multi-step prediction chain may also use the HPN to generate future hypotheses based on observation history. The safety prioritizer, integrated within the VFN, may be configured to penalize high-risk actions, masking them when selected, increasing safety. Additionally, the system may apply deep reinforcement learning for high-level policy creation for safe tactical decision-making. The method may optimize social utility and/or may increase sample efficiency and safety, making significant strides in autonomous vehicle operation.


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    Title :

    SYSTEM AND METHOD FOR AUTONOMOUS VEHICLE NAVIGATION IN MIXED-AUTONOMY TRAFFIC ENVIRONMENTS



    Publication date :

    2025-08-07


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion




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