Reinforcement and model learning for vehicle operation

A method for use in traversing a vehicle transportation network, the method comprising:

• traversing, by an autonomous vehicle, a vehicle transportation network, wherein traversing the vehicle transportation network includes:
• determining a route of the autonomous vehicle within the vehicle transportation network;
• executing the route of the autonomous vehicle;
• detecting an operational scenario based on the route of the autonomous vehicle and a location of the autonomous vehicle;
• determining a particular scenario-specific operation control evaluation module based on the operational scenario, wherein the scenario-specific operation control evaluation module includes models that determine a candidate vehicle control action based on an operational environment of the autonomous vehicle, wherein the models include an exploration model based on selecting a low probability action in a semi-random manner and an exploitation model based on selecting a high probability action;
• instantiating a scenario-specific operational control evaluation module instance based on the particular scenario-specific operation control evaluation module;
• traversing a portion of the vehicle transportation network by executing the candidate vehicle control action using the exploration model or the exploitation model;
• observing a state resulting from the execution of the candidate vehicle control action;
• updating the scenario-specific operational control evaluation module instance based on the state;
• generating a state-action history entry based on the candidate vehicle control action and the state;
• and
• storing the state-action history entry in a scenario-specific operation control database.