Abstract: The technology relates to assigning customer service requests for a fleet of autonomous vehicles providing trip services. For instance, a message having contents including information about a trip the vehicle is currently servicing may be received from a computing device of an autonomous vehicle of the fleet of vehicles. A request for customer service for the vehicle may be generated based on the contents of the message. A priority of the request may be determined based on the contents of the message. The request may be inserted into a queue based on the priority. The request may be assigned to a customer service representative based on a place of the request in the queue.

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 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 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: 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 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.