Techniques are described herein for executing driving simulations where control of simulated agents is switched between different programmatic planners based on different driving scenarios encountered in the simulation. As an example, a simulation system may execute a driving simulation including a programmatic agent initially controlled using a heuristic planner. During the execution of the simulation, the simulation system may detect one or more driving scenarios for which the heuristic planner is unable to navigate the environment or may determine an unrealistic trajectory for the simulated agent. Based on detecting a driving scenario, the simulation system may determine a machine-learned planner to control the simulated agent to navigate the driving scenario. After the driving scenario has been successfully traversed by the simulated agent using the machine-learned planner, the simulation system may switch the control of the simulated agent back to the heuristic planner to continue the simulation.


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    Title :

    Heuristic and machine learning agents in driving simulations


    Contributors:

    Publication date :

    2025-06-24


    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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