Abstract: Disclosed herein are system, method, and computer program product embodiments for handling unmapped speed limit signs. For example, the method includes receiving sensor data from a sensor of a vehicle, identifying a traffic sign within a field of view of the vehicle based on the sensor data, identifying one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map, and updating an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified sign is more restrictive than an attribute associated with the lane segment in the a priori map.

Abstract: Disclosed herein are system, method, and computer program product aspects for simulating map update functions in an autonomous vehicle (AV) system. The system can create a simulation environment to test the AV system using data collected during regular operations of the AV system. The data comprises (1) map updating documents from a cloud service, (2) local map updating documents, and (3) observation data. A map-deviation detection mechanism is used to process the observation data.

Abstract: Systems and methods for operating an autonomous vehicle (AV) are provided. The method includes detecting one or more objects in an environment, predicting a first set of predicted object trajectories comprising one or more trajectories for each of the detected one or more objects, generating a plurality of candidate AV trajectories for the AV, scoring each of the candidate AV trajectories according to a cost function, using the scoring to select a final AV trajectory for execution, determining which of the predicted object trajectories affected the final AV trajectory and which did not do so, adding the predicted object trajectories that affected the final AV trajectory to a persisted prediction cache, excluding from the persisted prediction cache any predicted object trajectories that did not affect the final AV trajectory, and executing the final AV trajectory to cause the AV to move along the final AV trajectory.

Abstract: Disclosed herein are system, method, and computer program product embodiments for handling traffic signs. For example, the method includes receiving sensor data from a sensor of a vehicle and identifying a traffic sign within a field of view of the vehicle based on the sensor data. The method also includes assigning a probable class to the identified sign based on a determination that the identified sign is not mapped in a priori map and a determination that a probability of existence of the sign is greater than a threshold and modifying a behavior of the vehicle based on the assigned probable class.

Abstract: Disclosed herein are system, method, and computer program product embodiments for handling unmapped speed limit signs. For example, the method includes receiving sensor data from a sensor of a vehicle, identifying a traffic sign within a field of view of the vehicle based on the sensor data, identifying one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map, and updating an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified sign is more restrictive than an attribute associated with the lane segment in the a priori map.

Abstract: Disclosed herein are system, method, and computer program product aspects for simulating map update functions in an autonomous vehicle (AV) system. The system can create a simulation environment to test the AV system using data collected during regular operations of the AV system. The data comprises (1) map updating documents from a cloud service, (2) local map updating documents, and (3) observation data. A map-deviation detection mechanism is used to process the observation data.

Abstract: Methods for planning a trajectory for an autonomous vehicle are disclosed. A vehicle motion planning system will determine a reference curve that represents a path via which the vehicle may travel. The system will detect an actor that is moving in the environment. The system will segment the reference curve according to time intervals. For each of the time intervals, the system will identify a bounding geometry for the actor, predict a lateral offset distance between the reference curve and the actor, and use the predicted lateral offset distance to determine whether to alter a planned trajectory for the autonomous vehicle.

Abstract: Methods, systems, and computer program products for navigating a vehicle are disclosed. The methods include extracting lane segment data associated with lane segments of a vector map that are within a region of interest, and analyzing the lane segment data and a heading of the vehicle to determine whether motion of the vehicle satisfies a condition. The condition can be associated with (i) an association between the heading of the vehicle and a direction of travel of a lane that corresponds to the current location of the vehicle and/or (ii) a minimum stopping distance to an imminent traffic control measure in the lane that corresponds to the current location of the vehicle. When the motion does not satisfy the condition, the methods include causing the vehicle to perform a motion correction.

Abstract: Systems and methods for operating an autonomous vehicle (AV) are provided. The method includes detecting one or more objects in an environment, predicting a first set of predicted object trajectories comprising one or more trajectories for each of the detected one or more objects, generating a plurality of candidate AV trajectories for the AV, scoring each of the candidate AV trajectories according to a cost function, using the scoring to select a final AV trajectory for execution, determining which of the predicted object trajectories affected the final AV trajectory and which did not do so, adding the predicted object trajectories that affected the final AV trajectory to a persisted prediction cache, excluding from the persisted prediction cache any predicted object trajectories that did not affect the final AV trajectory, and executing the final AV trajectory to cause the AV to move along the final AV trajectory.

Abstract: Methods, systems, and computer program products for navigating a vehicle are disclosed. The methods include extracting lane segment data associated with lane segments of a vector map that are within a region of interest, and analyzing the lane segment data and a heading of the vehicle to determine whether motion of the vehicle satisfies a condition. The condition can be associated with (i) an association between the heading of the vehicle and a direction of travel of a lane that corresponds to the current location of the vehicle and/or (ii) a minimum stopping distance to an imminent traffic control measure in the lane that corresponds to the current location of the vehicle. When the motion does not satisfy the condition, the methods include causing the vehicle to perform a motion correction.

Abstract: Vehicle driver assistance and warning systems that alert a driver of a vehicle to wrong-way driving and/or imminent traffic control measures (TCMs) are disclosed. The system will identify a region of interest around the vehicle, access a vector map that includes the region of interest, and extract lane segment data associated with lane segments that are within the region of interest. The system will analyze the lane segment data and the vehicle's direction of travel to determine whether motion of the vehicle indicates that either: (a) the vehicle is traveling in a wrong-way direction for its lane; or (b) the vehicle is within a minimum stopping distance to an imminent TCM in its lane. When the system detects either condition, it will cause a driver warning system of the vehicle to output a driver alert.

Abstract: Vehicle driver assistance and warning systems that alert a driver of a vehicle to wrong-way driving and/or imminent traffic control measures (TCMs) are disclosed. The system will identify a region of interest around the vehicle, access a vector map that includes the region of interest, and extract lane segment data associated with lane segments that are within the region of interest. The system will analyze the lane segment data and the vehicle's direction of travel to determine whether motion of the vehicle indicates that either: (a) the vehicle is traveling in a wrong-way direction for its lane; or (b) the vehicle is within a minimum stopping distance to an imminent TCM in its lane. When the system detects either condition, it will cause a driver warning system of the vehicle to output a driver alert.

Abstract: Methods for planning a trajectory for an autonomous vehicle are disclosed. A vehicle motion planning system will determine a reference curve that represents a path via which the vehicle may travel. The system will detect an actor that is moving in the environment. The system will segment the reference curve according to time intervals. For each of the time intervals, the system will identify a bounding geometry for the actor, predict a lateral offset distance between the reference curve and the actor, and use the predicted lateral offset distance to determine whether to alter a planned trajectory for the autonomous vehicle.