Abstract: Systems and methods for selecting a trajectory for an autonomous vehicle based on perceived risk are provided. A trajectory is selected that satisfies objective safety constraints and minimizes an overall cost based at least in part on cost components representing the perceived risk of the trajectory. The vehicle is navigated according to the selected (e.g., optimized) trajectory.

Abstract: The subject matter described in this specification is generally directed control architectures for an autonomous vehicle. In one example, a reference trajectory, a set of lateral constraints, and a set of speed constraints are received using a control circuit. The control circuit determines a set of steering commands based at least in part on the reference trajectory and the set of lateral constraints and a set of speed commands based at least in part on the set of speed constraints. The vehicle is navigated, using the control circuit, according to the set of steering commands and the set of speed commands.

Abstract: Provided are methods, systems, and computer program products for bidirectional path optimization in a grid. An example method may include: receiving vehicle environment data associated with an environment of a vehicle; determining an occupancy map of the environment using the vehicle environment data, the occupancy map identifying at least one obstacle in the environment; generating a reference path to a destination location for the vehicle; determining a travel path to an intermediate location in the occupancy map based at least in part on the reference path and a longitudinal direction variable, wherein the intermediate location is proximate a point on the reference path; and generating actuation commands for the vehicle based at least in part on the travel path.

Abstract: The subject matter described in this specification is generally directed control architectures for an autonomous vehicle. In one example, a reference trajectory, a set of lateral constraints, and a set of speed constraints are received using a control circuit. The control circuit determines a set of steering commands based at least in part on the reference trajectory and the set of lateral constraints and a set of speed commands based at least in part on the set of speed constraints. The vehicle is navigated, using the control circuit, according to the set of steering commands and the set of speed commands.

Abstract: In some aspects and/or embodiments, systems, methods, and computer program products described herein include and/or implement technology for encoding dynamic homotopy constraints in spatio-temporal grids, including a method comprising: determining a plurality of dynamic homotopy constraints associated with a scenario involving a vehicle in an environment; embedding the plurality of dynamic homotopy constraints in a plurality of spatio-temporal grids, where each spatio-temporal grid includes individual grids for each timestep of a prediction horizon, generating a plurality of trajectories based on the plurality of dynamic homotopy constraints embedded in the plurality of spatio-temporal grids; selecting a particular trajectory from among the plurality of trajectories generated; and controlling the vehicle in the environment based on the particular trajectory selected from among the plurality of trajectories.

Abstract: Systems and methods for selecting a trajectory for an autonomous vehicle based on perceived risk are provided. A trajectory is selected that satisfies objective safety constraints and minimizes an overall cost based at least in part on cost components representing the perceived risk of the trajectory. The vehicle is navigated according to the selected (e.g., optimized) trajectory.

Abstract: The subject matter described in this specification is generally directed to a system and techniques for controlling an autonomous vehicle. In one example, a proximity rule is received by a control circuit. A reference trajectory is received from the planning circuit by a control circuit, where the reference trajectory is determined by the planning circuit based on the proximity rule. The control circuit receives the proximity rule and determines a predicted trajectory based on the reference trajectory and the proximity rule. The autonomous vehicle is then navigated according to the predicted trajectory.

Abstract: Among other things, techniques are described for identifying, by at least one processor of a vehicle based on a graph that includes a plurality of edges and a plurality of nodes, a reference path through an environment that includes a subset of the plurality of edges. The technique further includes identifying a first path based on optimization of a spatial model related to the graph and the reference path and a second path based on application of at least one constraint to the reference path. The technique further includes selecting, by the at least one processor, the first path or the second path as a path along which the vehicle will traverse based on a pre-identified rulebook. Other embodiments may be described or claimed.

Abstract: The subject matter described in this specification is generally directed control architectures for an autonomous vehicle. In one example, a reference trajectory, a set of lateral constraints, and a set of speed constraints are received using a control circuit. The control circuit determines a set of steering commands based at least in part on the reference trajectory and the set of lateral constraints and a set of speed commands based at least in part on the set of speed constraints. The vehicle is navigated, using the control circuit, according to the set of steering commands and the set of speed commands.