Risk aware executor with action set recommendations

An autonomous vehicle comprising:

• a processor configured to execute instructions stored on a non-transitory computer readable medium to:
• instantiating respective decision component instances by instructions to:
• responsive to identifying a distinct vehicle operational of an intersection scenario, instantiate an intersection-decision component instance,
• wherein the intersection-decision component instance is an instance of an intersection- decision component modeling the intersection scenario, and
• wherein the intersection-decision component instance provides a first solution that is obtained offline in a first idealized situation that is decoupled from a current context of the autonomous vehicle;
• responsive to identifying a distinct vehicle operational of a pedestrian scenario, instantiate a pedestrian-decision component instance,
• wherein the pedestrian-decision component instance is an instance of a pedestrian-decision component modeling the pedestrian scenario, and
• wherein the instantiate a pedestrian-decision component instance provides a second solution that is obtained offline in a second idealized situation that is decoupled from the current context of the autonomous vehicle;
• and
• responsive to identifying a distinct vehicle operational of a lane-change scenario, instantiating a lane-change-decision component instance,
• wherein the lane-change-decision component instance is an instance of a lane-change-decision component modeling the lane-change scenario, and
• wherein the lane-change-decision component instance provides a third solution that is obtained offline in a third idealized situation that is decoupled from the current context of the autonomous vehicle;
• receive respective sets of candidate actions from the respective decision component instances, wherein each decision component instance is an instance of a decision component modeling a distinct vehicle operational scenario;
• identify an intersecting set of actions as an intersection of the respective sets of candidate actions;
• select an action from the intersecting set of actions based on respective priorities of the respective decision components;
• determine whether a current value of a state factor of the current context of the AV conflicts with a value of the state factor required for the action;
• response to determining that the current value of the state factor conflicts with the value required for the action, convert the action to another action;
• and
• control the autonomous vehicle to traverse a portion of a vehicle transportation network based on the action.

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

• receiving a first set of candidate actions from a first decision component instance and a second set of candidate actions from a second decision component instance,
• wherein the first decision component instance is a first instance of a first decision component modeling a first distinct vehicle operational scenario,
• wherein the first decision component instance provides a first solution to the first distinct vehicle operational scenario,
• wherein the first solution is obtained offline in a first idealized situation that is decoupled from a current context of an autonomous vehicle (AV),
• wherein the second decision component instance is a second instance of a second decision component modeling a second distinct vehicle operational scenario,
• wherein the second decision component instance provides a second solution to the second distinct vehicle operational scenario, and
• wherein the second solution is obtained offline in a second idealized situation that is decoupled from the current context of the AV;
• identifying an intersecting set of actions as an intersection of the first set of candidate actions and the second set of candidate actions;
• determining whether the intersecting set of actions is empty;
• responsive to determining that the intersecting set of actions is empty, adding a default action to the intersecting set of actions;
• selecting the action is conditioned on a context of state vectors associated with the autonomous vehicle, wherein selecting the action comprises:
• determining whether a current value of a state factor of the current context of the AV conflicts with a value of the state factor required for the action;
• and
• response to determining that the current value of the state factor conflicts with the value required for the action, converting the action to another action;
• and
• controlling the autonomous vehicle to traverse a portion of the vehicle transportation network based on the action.