Abstract: A method includes obtaining historical information for a plurality of past trips that are completed by a fleet of vehicles. The historical information includes request times, origins, and destinations corresponding to the plurality of past trips completed by the fleet of vehicles. The method also includes generating a scenario based on the historical information, and performing a simulation based on the scenario. The simulation includes applying a first dispatching service and a first routing service to the scenario. The method further includes using the simulation to compare the first dispatching service to a second dispatching service and providing the comparison to a user.

Abstract: Systems and methods for generating a composite map are provided. In one aspect, a method is provided that includes identifying a first node and a source node on a first map. The method further includes determining a candidate source node on a second map that corresponds to the source node on the first map. The method further includes determining a plurality of candidate nodes on the second map that potentially correspond to the first node and selecting a respective candidate node from the plurality of candidate nodes based on a similarity of a routing distance between: the respective candidate node and the candidate source node on the second map and the first node and the source node on the first map. The method may also include connecting the selected respective candidate node and the first node and combining the first map and the second map into a composite map.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that solves gridlock as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can determine one or more keep clear areas associated with the lane sequence, each keep clear area indicative of a region along the nominal path in which gridlock prevention is desired. A gridlock constraint can be generated for each of the one or more keep clear areas, each constraint being defined as a constraint area in a multi-dimensional space. A low-cost trajectory path can be determined through a portion of the multi-dimensional space that minimizes exposure to the constraint areas and that is consistent with all constraints generated for the one or more objects of interest and the one or more keep clear areas.

Abstract: Systems and methods for generating a composite map are provided. In one aspect, a method is provided that includes identifying a first node and a source node on a first map. The method further includes determining a candidate source node on a second map that corresponds to the source node on the first map. The method further includes determining a plurality of candidate nodes on the second map that potentially correspond to the first node and selecting a respective candidate node from the plurality of candidate nodes based on a similarity of a routing distance between: the respective candidate node and the candidate source node on the second map and the first node and the source node on the first map. The method may also include connecting the selected respective candidate node and the first node and combining the first map and the second map into a composite map.

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 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: Systems and methods for generating a composite map are provided. In one aspect, a method is provided that includes identifying a first node and a source node on a first map. The method further includes determining a candidate source node on a second map that corresponds to the source node on the first map. The method further includes determining a plurality of candidate nodes on the second map that potentially correspond to the first node and selecting a respective candidate node from the plurality of candidate nodes based on a similarity of a routing distance between: the respective candidate node and the candidate source node on the second map and the first node and the source node on the first map. The method may also include connecting the selected respective candidate node and the first node and combining the first map and the second map into a composite map.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that solves gridlock as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can determine one or more keep clear areas associated with the lane sequence, each keep clear area indicative of a region along the nominal path in which gridlock prevention is desired. A gridlock constraint can be generated for each of the one or more keep clear areas, each constraint being defined as a constraint area in a multi-dimensional space. A low-cost trajectory path can be determined through a portion of the multi-dimensional space that minimizes exposure to the constraint areas and that is consistent with all constraints generated for the one or more objects of interest and the one or more keep clear areas.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that solves gridlock as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can determine one or more keep clear areas associated with the lane sequence, each keep clear area indicative of a region along the nominal path in which gridlock prevention is desired. A gridlock constraint can be generated for each of the one or more keep clear areas, each constraint being defined as a constraint area in a multi-dimensional space. A low-cost trajectory path can be determined through a portion of the multi-dimensional space that minimizes exposure to the constraint areas and that is consistent with all constraints generated for the one or more objects of interest and the one or more keep clear areas.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that solves gridlock as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can determine one or more keep clear areas associated with the lane sequence, each keep clear area indicative of a region along the nominal path in which gridlock prevention is desired. A gridlock constraint can be generated for each of the one or more keep clear areas, each constraint being defined as a constraint area in a multi-dimensional space. A low-cost trajectory path can be determined through a portion of the multi-dimensional space that minimizes exposure to the constraint areas and that is consistent with all constraints generated for the one or more objects of interest and the one or more keep clear areas.

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: 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.