Abstract: Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.

Abstract: A method is provided for managing and tracking scouting tasks to obtain map information using a fleet of autonomous vehicles. For instance, the method includes defining a scouting quest to obtain the map information. The scouting quest includes a plurality of objectives. Each objective is associated with a geographic location from which sensor data is to be captured. The method also includes receiving a first update message from an autonomous vehicle of the fleet. The update message identifies a location of the autonomous vehicle. The method also includes assigning at least one of the objectives to the autonomous vehicle based on the location of the autonomous vehicle. The method also includes sending instructions to the autonomous vehicle in order to cause the autonomous vehicle to complete the at least one objective and after sending, tracking a status of the scouting quest.

Abstract: Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.

Abstract: Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Abstract: Aspects of the disclosure relate to assigning a fleet of driverless vehicles to a plurality of parking locations for parking vehicles of the fleet. For instance, locations of the vehicles of the fleet as well as a number of available spaces at each of the plurality of parking location locations may be tracked. A subset of the fleet not already located at one of the plurality of parking locations is identified. At least one assignment assigning each vehicle of the subset to a respective parking location of the plurality of parking locations is determined according to the numbers of available spaces and the identified locations of the subset. For the at least one assignment, a total cost is determined by determining a cost value for each of a plurality of factors. The given assignment is sent to the fleet based on the total cost and the cost value.

Abstract: Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Abstract: Aspects of the disclosure relate to arranging a pick up and drop off locations between a driverless vehicle and a passenger. As an example, a method of doing so may include receiving a request for a vehicle from a client computing device, wherein the request identifies a first location. Pre-stored map information and the first location are used to identify a recommended point according to a set of heuristics. Each heuristic of the set of heuristics has a ranking such that the recommended point corresponds to a location that satisfies at least one of the heuristics having a first rank and such that no other location satisfies any other heuristic of the set of heuristics having a higher rank than the first rank. The pre-stored map information identifying a plurality of pre-determined locations for the vehicle to stop, and the recommended point is one of the plurality of pre-determined locations.

Abstract: Aspects of the disclosure relate to arranging a pick up and drop off locations between a driverless vehicle and a passenger. As an example, a method of doing so may include receiving a request for a vehicle from a client computing device, wherein the request identifies a first location. Pre-stored map information and the first location are used to identify a recommended point according to a set of heuristics. Each heuristic of the set of heuristics has a ranking such that the recommended point corresponds to a location that satisfies at least one of the heuristics having a first rank and such that no other location satisfies any other heuristic of the set of heuristics having a higher rank than the first rank. The pre-stored map information identifying a plurality of pre-determined locations for the vehicle to stop, and the recommended point is one of the plurality of pre-determined locations.

Abstract: Aspects of the disclosure relate to assigning a fleet of driverless vehicles to a plurality of parking locations for parking vehicles of the fleet. For instance, locations of the vehicles of the fleet as well as a number of available spaces at each of the plurality of parking location locations may be tracked. A subset of the fleet not already located at one of the plurality of parking locations is identified. At least one assignment assigning each vehicle of the subset to a respective parking location of the plurality of parking locations is determined according to the numbers of available spaces and the identified locations of the subset. For the at least one assignment, a total cost is determined by determining a cost value for each of a plurality of factors. The given assignment is sent to the fleet based on the total cost and the cost value.

Abstract: Aspects of the disclosure relate to arranging a pick up and drop off locations between a driverless vehicle and a passenger. As an example, a method of doing so may include receiving a request for a vehicle from a client computing device, wherein the request identifies a first location. Pre-stored map information and the first location are used to identify a recommended point according to a set of heuristics. Each heuristic of the set of heuristics has a ranking such that the recommended point corresponds to a location that satisfies at least one of the heuristics having a first rank and such that no other location satisfies any other heuristic of the set of heuristics having a higher rank than the first rank. The pre-stored map information identifying a plurality of pre-determined locations for the vehicle to stop, and the recommended point is one of the plurality of pre-determined locations.

Abstract: Aspects of the disclosure relate to assigning a fleet of driverless vehicles to a plurality of parking locations for parking vehicles of the fleet. For instance, locations of the vehicles of the fleet as well as a number of available spaces at each of the plurality of parking location locations may be tracked. A subset of the fleet not already located at one of the plurality of parking locations is identified. At least one assignment assigning each vehicle of the subset to a respective parking location of the plurality of parking locations is determined according to the numbers of available spaces and the identified locations of the subset. For the at least one assignment, a total cost is determined by determining a cost value for each of a plurality of factors. The given assignment is sent to the fleet based on the total cost and the cost value.

Abstract: Aspects of the disclosure relate to determining vehicle operation modes for a fleet of vehicles. This may include maintaining a storage system including vehicle parameters for a vehicle fleet such that each vehicle of the fleet is associated with a set of vehicle parameters. The vehicle operation mode may be determined by selecting one of a plurality of vehicle operation levels arranged in a hierarchy or by identifying a set of tags where each level or tag corresponds to a vehicle driving capability. The determined vehicle operation mode may be communicated to the given vehicle in order to cause the vehicle to operate according to the determined vehicle operation mode.

Abstract: A method is provided for managing and tracking scouting tasks to obtain map information using a fleet of autonomous vehicles. For instance, the method includes defining a scouting quest to obtain the map information. The scouting quest includes a plurality of objectives. Each objective is associated with a geographic location from which sensor data is to be captured. The method also includes receiving a first update message from an autonomous vehicle of the fleet. The update message identifies a location of the autonomous vehicle. The method also includes assigning at least one of the objectives to the autonomous vehicle based on the location of the autonomous vehicle. The method also includes, sending instructions to the autonomous vehicle in order to cause the autonomous vehicle to complete the at least one objective and after sending, tracking a status of the scouting quest.

Abstract: Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.

Abstract: Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Abstract: Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.

Abstract: Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Abstract: Aspects of the disclosure relate to assigning a fleet of driverless vehicles to a plurality of parking locations for parking vehicles of the fleet. For instance, locations of the vehicles of the fleet as well as a number of available spaces at each of the plurality of parking location locations may be tracked. A subset of the fleet not already located at one of the plurality of parking locations is identified. At least one assignment assigning each vehicle of the subset to a respective parking location of the plurality of parking locations is determined according to the numbers of available spaces and the identified locations of the subset. For the at least one assignment, a total cost is determined by determining a cost value for each of a plurality of factors. The given assignment is sent to the fleet based on the total cost and the cost value.

Abstract: Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.

Abstract: Aspects of the disclosure relate to arranging a pick up and drop off locations between a driverless vehicle and a passenger. As an example, a method of doing so may include receiving a request for a vehicle from a client computing device, wherein the request identifies a first location. Pre-stored map information and the first location are used to identify a recommended point according to a set of heuristics. Each heuristic of the set of heuristics has a ranking such that the recommended point corresponds to a location that satisfies at least one of the heuristics having a first rank and such that no other location satisfies any other heuristic of the set of heuristics having a higher rank than the first rank. The pre-stored map information identifying a plurality of pre-determined locations for the vehicle to stop, and the recommended point is one of the plurality of pre-determined locations.