Autonomous vehicles (AVs) may need to contend with conflicting traveling rules and the AV controller would need to select the least objectionable control action. A rank-preserving reward function can be applied to trajectories derived from a rule hierarchy. The reward function can be correlated to a robustness vector derived for each trajectory. Thereby the highest ranked rules would result in the highest reward, and the lower ranked rules would result in lower reward. In some aspects, one or more optimizers, such as a stochastic optimizer can be utilized to improve the results of the reward calculation. In some aspects, a sigmoid function can be applied to the calculation to smooth out the step function used to calculate the robustness vector. The preferred trajectory selected using the results from the reward function can be communicated to an AV controller for implementation as a control action.


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    Title :

    EGO TRAJECTORY PLANNING WITH RULE HIERARCHIES FOR AUTONOMOUS VEHICLES


    Contributors:
    VEER SUSHANT (author) / LEUNG KAREN (author) / COSNER RYAN (author) / CHEN YUXIAO (author) / PAVONE MARCO (author)

    Publication date :

    2024-06-20


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    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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