Objective-based reasoning in autonomous vehicle decision-making

An autonomous vehicle comprising:

• a processor configured to execute instructions stored on a non-transitory computer readable medium to:
• operate a scenario-specific operational control evaluation module instance, wherein the scenario-specific operational control evaluation module instance includes an instance of a scenario-specific operational control evaluation model of a distinct vehicle operational scenario, and wherein operating the scenario-specific operational control evaluation module instance includes identifying a multi-objective policy for the scenario-specific operational control evaluation model, wherein the multi-objective policy includes at least a first objective, a second objective, and a topological graph that shows a relationship between the first objective and the second objective;
• receive, from the multi-objective policy for the scenario-specific operational control evaluation module instance, a candidate vehicle control action associated with the first objective and a candidate vehicle control action associated with the second objective;
• determine a buffer value associated with the first objective and the second objective;
• determine a probability of success of each of the first objective and the second objective based on a competence measure that is incorporated into a partially observable Markov decision process (POMDP) state transition to obtain a restricted number of available actions
• select a vehicle control action from the restricted number of available actions based on the buffer value, wherein the selected vehicle control action is the candidate vehicle control action associated with the first objective or the candidate vehicle control action associated with the second objective;
• and
• cause the autonomous vehicle to perform the selected vehicle control action to traverse a portion of a vehicle transportation network.

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

• traversing the vehicle transportation network, by an autonomous vehicle, wherein traversing the vehicle transportation network includes:
• operating a scenario-specific operational control evaluation module instance, wherein the scenario-specific operational control evaluation module instance includes an instance of a scenario-specific operational control evaluation model of a distinct vehicle operational scenario, and wherein operating the scenario-specific operational control evaluation module instance includes identifying a multi-objective policy for the scenario-specific operational control evaluation model, wherein the multi-objective policy includes a topological graph that shows a relationship between at least two objectives;
• receiving, from the multi-objective policy for the scenario-specific operational control evaluation module instance, candidate vehicle control actions associated with each of the at least two objectives;
• determining a probability of success of each of the at least two objectives based on a competence measure that is incorporated into a partially observable Markov decision process (POMDP) state transition to obtain a restricted number of available actions;
• selecting a vehicle control action from the restricted number of available actions based on a buffer value, wherein the selected vehicle control action is one of the candidate vehicle control actions;
• and
• traversing a portion of the vehicle transportation network by performing the selected vehicle control action.