Abstract: Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The system receives a base simulation scenario with features of a scene through which a vehicle may travel. The system then generates an augmentation element with a simulated behavior for an object in the scene by: (i) accessing a data store in which behavior probabilities are mapped to object types to retrieve a set of behavior probabilities for the object; and (ii) applying a randomization function to the behavior probabilities to select the simulated behavior for the object. The system will add the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The system will then apply the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model.

Abstract: A method includes receiving a base simulation scenario that includes features of a scene through which a vehicle may travel and receiving a simulation variation for an object in the scene. The simulation variation defines multiple values for a characteristic of the object. The method includes adding the simulation variation to the base simulation scenario to yield an augmented simulation scenario and applying the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model. The motion planning model iteratively simulates variations of the object based on values for the characteristic of the object. In response to each simulated variation of the object, the motion planning model selects a continued trajectory for the vehicle, wherein the continued trajectory is either the planned trajectory or an alternate trajectory.

Abstract: Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The method receives a base simulation scenario with features of a scene through which a vehicle may travel, defines an interaction zone in the scene, generates an augmentation element that includes an object and a behavior for the object, and adds the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The augmented simulation scenario is applied to a vehicle motion planning model to train the model.

Abstract: Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The system receives a base simulation scenario with features of a scene through which a vehicle may travel. The system then generates an augmentation element with a simulated behavior for an object in the scene by: (i) accessing a data store in which behavior probabilities are mapped to object types to retrieve a set of behavior probabilities for the object; and (ii) applying a randomization function to the behavior probabilities to select the simulated behavior for the object. The system will add the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The system will then apply the augmented simulation scenario to an autonomous vehicle motion planning model to train the motion planning model.

Abstract: Systems and methods for map quality assurance and/or vehicle control. The methods comprise: generating, by the computing device, a plurality of simulation routes for a vehicle to traverse in a map; simulating, by the computing device, operations of the vehicle along each route of the plurality of simulation routes in the map; analyzing, by the computing device, results from the simulating to validate whether or not a quality of the map is validated; causing, by the computing device, the map to be used to control autonomous or semi-autonomous operations of the vehicle, when a determination is made that the quality of the map is validated; and performing a given operation other than said causing, when a determination is made that the quality of the map is not validated.