Abstract: A method includes of routing an autonomous vehicle includes receiving information obtained from a camera on a second vehicle distinct from the autonomous vehicle. The method includes automatically identifying a road condition using image analysis of the information received from the camera on the second vehicle. The method includes receiving a request to route the autonomous vehicle from a first location to a second location; and in response to the request: generating a cost model for routing the autonomous vehicle, wherein the cost model includes a cost of the road condition automatically identified from the information received from the camera on the second vehicle; selecting a route from the first location to the second location in accordance with the cost model; and routing an autonomous vehicle in accordance with the selected route.

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: 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: A method includes of routing an autonomous vehicle includes receiving information obtained from a camera on a second vehicle distinct from the autonomous vehicle. The method includes automatically identifying a road condition using image analysis of the information received from the camera on the second vehicle. The method includes receiving a request to route the autonomous vehicle from a first location to a second location; and in response to the request: generating a cost model for routing the autonomous vehicle, wherein the cost model includes a cost of the road condition automatically identified from the information received from the camera on the second vehicle; selecting a route from the first location to the second location in accordance with the cost model; and routing an autonomous vehicle in accordance with the selected route.

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: A method includes of routing an autonomous vehicle includes receiving information obtained from a camera on a second vehicle distinct from the autonomous vehicle. The method includes automatically identifying a road condition using image analysis of the information received from the camera on the second vehicle. The method includes receiving a request to route the autonomous vehicle from a first location to a second location; and in response to the request: generating a cost model for routing the autonomous vehicle, wherein the cost model includes a cost of the road condition automatically identified from the information received from the camera on the second vehicle; selecting a route from the first location to the second location in accordance with the cost model; and routing an autonomous vehicle in accordance with the selected route.

Abstract: A method includes storing representations of a passengers and fleet vehicles. The method includes generating a graph representation of a geographic map that includes requested pick-up locations and drop-off locations for the passengers and generating a state graph representation of the passengers and the fleet vehicles. The state graph representation includes a plurality of nodes connected by edges. Each of the plurality of nodes represents a candidate state of the passengers and the fleet vehicles. A respective edge of the state graph representation represents an action of a respective vehicle picking up or dropping off a passenger. The respective edge has a cost that is based at least in part on traversal of the graph representation of the geographic map. The method further includes using the state graph representation to generate a set of routes and route the fleet vehicles in accordance with the generated set of routes.

Abstract: A method includes of routing an autonomous vehicle includes receiving information obtained from a camera on a second vehicle distinct from the autonomous vehicle. The method includes automatically identifying a road condition using image analysis of the information received from the camera on the second vehicle. The method includes receiving a request to route the autonomous vehicle from a first location to a second location; and in response to the request: generating a cost model for routing the autonomous vehicle, wherein the cost model includes a cost of the road condition automatically identified from the information received from the camera on the second vehicle; selecting a route from the first location to the second location in accordance with the cost model; and routing an autonomous vehicle in accordance with the selected route.

Abstract: A method includes of routing an autonomous vehicle includes receiving information obtained from a camera on a second vehicle distinct from the autonomous vehicle. The method includes automatically identifying a road condition using image analysis of the information received from the camera on the second vehicle. The method includes receiving a request to route the autonomous vehicle from a first location to a second location; and in response to the request: generating a cost model for routing the autonomous vehicle, wherein the cost model includes a cost of the road condition automatically identified from the information received from the camera on the second vehicle; selecting a route from the first location to the second location in accordance with the cost model; and routing an autonomous vehicle in accordance with the selected route.

Abstract: A method includes storing representations of a passengers and fleet vehicles. The method includes generating a graph representation of a geographic map that includes requested pick-up locations and drop-off locations for the passengers and generating a state graph representation of the passengers and the fleet vehicles. The state graph representation includes a plurality of nodes connected by edges. Each of the plurality of nodes represents a candidate state of the passengers and the fleet vehicles. A respective edge of the state graph representation represents an action of a respective vehicle picking up or dropping off a passenger. The respective edge has a cost that is based at least in part on traversal of the graph representation of the geographic map. The method further includes using the state graph representation to generate a set of routes and route the fleet vehicles in accordance with the generated set of routes.

Abstract: A method includes generating a cost model for routing an autonomous vehicle. The cost model includes, for an intersection, a plurality of costs for distinct maneuvers through the intersection. The cost model is represented as a graph of nodes and edges, the edges having respective edge weights that represent costs in the cost model. Each edge of the representation of the intersection represents a respective maneuver through the intersection. The method further includes, in response to a request to route an autonomous vehicle: selecting a route in accordance with the cost model, wherein the selecting is based at least in part on one of the plurality of costs for the distinct maneuvers through the intersection; and routing the autonomous vehicle in accordance with the selected route.

Abstract: A method includes generating a cost model for routing an autonomous vehicle. The cost model includes, for an intersection, a plurality of costs for distinct maneuvers through the intersection. The cost model is represented as a graph of nodes and edges, the edges having respective edge weights that represent costs in the cost model. Each edge of the representation of the intersection represents a respective maneuver through the intersection. The method further includes, in response to a request to route an autonomous vehicle: selecting a route in accordance with the cost model, wherein the selecting is based at least in part on one of the plurality of costs for the distinct maneuvers through the intersection; and routing the autonomous vehicle in accordance with the selected route.

Abstract: Systems and methods for routing an autonomous vehicle are provided. In one aspect, a method is provided that includes generating a cost model for routing the autonomous vehicle. The cost model includes one or more costs other than travel time. The one or more costs other than travel time may include, for example, a cost of traversing an area where autonomous driving is prohibited, a cost of a characteristic of the autonomous vehicle or a cost of a road lacking lane lines. The method further includes receiving a request to route the autonomous vehicle from a first location to a second location. The method further includes, in response to the request to route the autonomous vehicle, selecting a route from the first location to the second location in accordance with the cost model and routing the autonomous vehicle along the selected route.