Abstract: The present disclosure provides autonomous vehicles that include a vehicle intention system that provides intention signals indicative of an intention of the autonomous vehicle. In particular, in one example, the vehicle intention system can obtain one or more operational messages from various systems or components of an autonomous vehicle that operate to control the autonomous vehicle. The operational messages can include operational data regarding the control or operation of the autonomous vehicle. The vehicle intention system can determine an intention of the autonomous vehicle based at least in part on the one or more operational messages. The vehicle intention system can output one or more intention signals that indicate the determined intention of the autonomous vehicle. For example, the vehicle intention system can publish intention messages that indicate the determined intention to one or more components or systems that consume the intention messages.

Abstract: The present disclosure provides autonomous vehicles that include a vehicle intention system that provides intention signals indicative of an intention of the autonomous vehicle. In particular, in one example, the vehicle intention system can obtain one or more operational messages from various systems or components of an autonomous vehicle that operate to control the autonomous vehicle. The operational messages can include operational data regarding the control or operation of the autonomous vehicle. The vehicle intention system can determine an intention of the autonomous vehicle based at least in part on the one or more operational messages. The vehicle intention system can output one or more intention signals that indicate the determined intention of the autonomous vehicle. For example, the vehicle intention system can publish intention messages that indicate the determined intention to one or more components or systems that consume the intention messages.

Abstract: Systems and methods are directed to lane change control for an autonomous vehicle. In one example, a computer-implemented method for determining whether to abort a lane change in an autonomous vehicle includes initiating, by a computing system comprising one or more computing devices, a lane change procedure for an autonomous vehicle. The method further includes obtaining, by the computing system, data indicative of one or more changed objects relative to the autonomous vehicle. The method further includes determining, by the computing system, that the lane change procedure cannot be completed by the autonomous vehicle based at least in part on the data indicative of one or more changed objects. The method further includes in response to determining that the lane change cannot be completed by the autonomous vehicle, generating, by the computing system, a motion plan that controls the autonomous vehicle to abort the lane change procedure.

Abstract: An autonomous vehicle (AV) includes a vehicle computing system including one or more processors programmed to receive map data associated with a map of a geographic location, including, one or more local routes in the one or more roadways between the current location of the AV and one or more exit locations, receive sensor data associated with an object detected in an environment surrounding the AV, select a local route of the one or more local routes based on the sensor data and control travel of the AV based on a selected local route of the one or more local routes. The map includes one or more roadways in the geographic location. The one or more exit locations are located between the current location of the AV and the destination location of the AV in a global route in the one or more roadways.

Abstract: An autonomous vehicle (AV) includes a vehicle computing system including one or more processors programmed to receive map data associated with a map of a geographic location, determine, based on the map data, one or more local routes in the one or more roadways between the current location of the AV and one or more exit locations, and control travel of the AV based on a selected local route of the one or more local routes. The map includes one or more roadways in the geographic location. The map data includes a global route in the one or more roadways between a current location of the AV and a destination location of the AV. The one or more exit locations are located between the current location of the AV and the destination location of the AV.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that generates constraints as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can generate constraints based on where objects of interest are predicted to be relative to an autonomous vehicle. A constraint solver can identify navigation decisions for each of the constraints that provide a consistent solution across all constraints. The solution provided. by the constraint solver can be in the form of a trajectory path determined relative to constraint areas for all objects of interest. The trajectory path represents a set of navigation decisions such that a navigation decision relative to one constraint doesn't sacrifice an ability to satisfy a different navigation decision relative to one or more other constraints.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that generates constraints as part of determining a motion plan for an autonomous vehicle (AV). In particular, a constraint solver determines a multi-dimensional space for each phase of a plurality of different phases of a lane change maneuver. For each different phase, objects of interest interacting with first and second lanes of the nominal path can be determined and constraints can be respectively generated. A portion of the multi-dimensional space including corresponding constraints that applies to a respective timeframe associated with each phase can be determined. The respective portions of the multi-dimensional space including corresponding constraints for each phase of the plurality of different phases of the lane change maneuver can be combined to generate a multiplexed space through which a low-cost trajectory path can be determined.

Abstract: A method for receiving autonomous vehicle (AV) driving path data associated with a driving path in a roadway of a geographic location. The driving path data associated with a trajectory for an AV in a roadway and trajectory points in a trajectory of the driving path in the roadway for determining at least one feature of the roadway positioned a lateral distance from a first trajectory of the one or more trajectories of the driving path of an AV based on the map data. The method includes receiving map data associated with a map of a geographic location, determining a driving path for an AV in a roadway, generating driving path information based on a trajectory point in a trajectory of the driving path, and providing driving path data associated with the driving path to an AV for controlling the AV on the roadway.

Abstract: Systems and methods are directed to lane change control for an autonomous vehicle. In one example, a computer-implemented method for determining whether to abort a lane change in an autonomous vehicle includes initiating, by a computing system comprising one or more computing devices, a lane change procedure for an autonomous vehicle. The method further includes obtaining, by the computing system, data indicative of one or more changed objects relative to the autonomous vehicle. The method further includes determining, by the computing system, that the lane change procedure cannot be completed by the autonomous vehicle based at least in part on the data indicative of one or more changed objects. The method further includes in response to determining that the lane change cannot be completed by the autonomous vehicle, generating, by the computing system, a motion plan that controls the autonomous vehicle to abort the lane change procedure.

Abstract: Systems and methods are directed to performing lane changes around a static or slow moving vehicle by an autonomous vehicle. In one example, a computer-implemented method for executing a lane change by an autonomous vehicle includes obtaining, by a computing system comprising one or more computing devices, an indication of an obstacle ahead of the autonomous vehicle in a current lane. The method further includes obtaining, by the computing system, an indication that the autonomous vehicle is likely to be queued behind the obstacle if staying in the current lane. The method further includes determining, by the computing system, that a lane change can be executed by the autonomous vehicle to move around the obstacle; and in response to determining that the lane change can be executed by the autonomous vehicle to move around the obstacle, generating a motion plan that executes the lane change.

Abstract: The present disclosure provides autonomous vehicles that include a vehicle intention system that provides intention signals indicative of an intention of the autonomous vehicle. In particular, in one example, the vehicle intention system can obtain one or more operational messages from various systems or components of an autonomous vehicle that operate to control the autonomous vehicle. The operational messages can include operational data regarding the control or operation of the autonomous vehicle. The vehicle intention system can determine an intention of the autonomous vehicle based at least in part on the one or more operational messages. The vehicle intention system can output one or more intention signals that indicate the determined intention of the autonomous vehicle. For example, the vehicle intention system can publish intention messages that indicate the determined intention to one or more components or systems that consume the intention messages.

Abstract: Systems and methods for controlling an autonomous vehicle to assist another autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining data representing a vehicle route of a first autonomous vehicle, wherein the first autonomous vehicle travels along the vehicle route from a first location to a second location. The method includes obtaining data representing an occlusion point that affects an operation of the first autonomous vehicle along the vehicle route. The method includes selecting a second autonomous vehicle, based at least in part on (i) the vehicle route and (ii) the occlusion point, to assist the first autonomous vehicle. The method includes deploying the second autonomous vehicle to assist the first autonomous vehicle to travel along the vehicle route.