Abstract: In one or more embodiments, one or more systems, methods, and/or processes may determine that a first vehicle is unsafe to continue navigating to the drop-off location while the first vehicle is traveling en-route to transport one or more passengers to a drop-off location. Based on this determination, an intermediate area for the one or more passengers to be dropped off by the first vehicle and picked up by a second vehicle is determined. Instructions are then provided to the first vehicle to cause the first vehicle to navigate to the intermediate area. Further, instructions are provided to the second vehicle to navigate at least in proximity to the intermediate area to pick up the one or more passengers, and navigate to the drop-off location after picking up the one or more passengers.

Abstract: In one embodiment, a method includes determining a fleet-level objective for a vehicle associated with instructing the vehicle to travel a route according to route criteria based on the fleet-level objective. The method includes receiving a ride request from a ride requestor associated with ride criteria including a pick-up location and a drop-off location. The method includes determining that the ride requestor is a passenger for the vehicle to satisfy the fleet-level objective contingent on modifications to the ride criteria. The method includes providing incentives to the ride requestor contingent on acceptance of the modifications to the ride criteria. The method includes, after receiving the acceptance of the modifications to the ride criteria, modifying the ride criteria in accordance with the route criteria. The method includes instructing the vehicle to transport the ride requestor based on the modified ride criteria so as to fulfill the fleet-level objective.

Abstract: In particular embodiments, a computing system may determine a predicted amount of ride requests for a plurality of collectively-managed vehicles and determine an availability of the collectively-managed vehicles to satisfy the predicted amount of ride requests. Subsequent to determining that the availability fails to satisfy one or more predetermined criteria for servicing the predicted amount of ride requests, the system may determine status information associated with the collectively-managed vehicles and determine, based on at least the status information, one or more minimum services for servicing one or more vehicles among the plurality of collectively-managed vehicles at one or more service centers such that the availability satisfies the one or more predetermined criteria. The system may instruct the one or more vehicles that are to receive the one or more minimum services to travel to the one or more service centers to be serviced.

Abstract: In one embodiment, a system includes one or more processors and one or more computer-readable non-transitory storage media coupled to one or more of the processors. The one or more computer-readable non-transitory storage media include instructions operable when executed by one or more of the processors to cause the system to perform operations including receiving service-facility data associated with a service facility that includes one or more service regions for servicing autonomous vehicles. Each of the one or more service regions is configured to charge an autonomous vehicle. The service facility data includes location information indicating a location of each of the one or more service regions; and availability information indicating an availability of each of the one or more service regions. The operations also include receiving vehicle data associated with a number of autonomous vehicles. The vehicle data includes a charge level of a respective autonomous vehicle.

Abstract: In one embodiment, a facility for calibrating sensors of an autonomous vehicle (AV) includes a camera calibration target configured to be measured by and used for calibrating an optical camera of the AV; a light detection and ranging (LiDAR) calibration target configured to be measured by and used for calibrating a LiDAR transceiver of the AV; and a platform configured to allow the AV to drive onto and park on the platform. The camera calibration target and the LiDAR calibration target are positioned to be detectable by the optical camera and the LiDAR transceiver while the AV is parked on the platform. The platform is further configured to modify a lateral position, height, or orientation of the optical camera and the LiDAR transceiver relative to the camera calibration target and the LiDAR calibration target while the AV is parked on the platform.

Abstract: In particular embodiments, a computing system may determine a predicted amount of ride requests for a plurality of collectively-managed vehicles and determine an availability of the collectively-managed vehicles to satisfy the predicted amount of ride requests. Subsequent to determining that the availability fails to satisfy one or more predetermined criteria for servicing the predicted amount of ride requests, the system may determine status information associated with the collectively-managed vehicles and determine, based on at least the status information, one or more minimum services for servicing one or more vehicles among the plurality of collectively-managed vehicles at one or more service centers such that the availability satisfies the one or more predetermined criteria. The system may instruct the one or more vehicles that are to receive the one or more minimum services to travel to the one or more service centers to be serviced.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may determine that a first vehicle is unsafe to continue navigating to the drop-off location while the first vehicle is traveling en-route to transport one or more passengers to a drop-off location. Based on this determination, an intermediate area for the one or more passengers to be dropped off by the first vehicle and picked up by a second vehicle is determined. Instructions are then provided to the first vehicle to cause the first vehicle to navigate to the intermediate area. Further, instructions are provided to the second vehicle to navigate at least in proximity to the intermediate area to pick up the one or more passengers, and navigate to the drop-off location after picking up the one or more passengers.

Abstract: In one embodiment, a facility for calibrating sensors of an autonomous vehicle (AV) includes a camera calibration target configured to be measured by and used for calibrating an optical camera of the AV; a light detection and ranging (LiDAR) calibration target configured to be measured by and used for calibrating a LiDAR transceiver of the AV; and a platform configured to allow the AV to drive onto and park on the platform. The camera calibration target and the LiDAR calibration target are positioned to be detectable by the optical camera and the LiDAR transceiver while the AV is parked on the platform. The platform is further configured to modify a lateral position, height, or orientation of the optical camera and the LiDAR transceiver relative to the camera calibration target and the LiDAR calibration target while the AV is parked on the platform.

Abstract: In one embodiment, a method includes receiving sensor data from one or more sensors of an autonomous vehicle (AV); determining that a first sensor of the one or more sensors needs recalibration based on the sensor data. The first sensor being of a first sensor type. The method also includes sending a request to a remote management system indicating that one or more of the sensors of the AV need recalibration and a location of the AV; determining the presence of a service vehicle having a calibration target configured to calibrate sensors of the first sensor type; and initiating a calibration routine using the calibration target.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may determine that a first vehicle is unsafe to continue navigating to the drop-off location while the first vehicle is traveling en-route to transport one or more passengers to a drop-off location. Based on this determination, an intermediate area for the one or more passengers to be dropped off by the first vehicle and picked up by a second vehicle is determined. Instructions are then provided to the first vehicle to cause the first vehicle to navigate to the intermediate area. Further, instructions are provided to the second vehicle to navigate at least in proximity to the intermediate area to pick up the one or more passengers, and navigate to the drop-off location after picking up the one or more passengers.

Abstract: In one embodiment, a method includes determining a fleet-level objective for a vehicle associated with instructing the vehicle to travel a route according to route criteria based on the fleet-level objective. The method includes receiving a ride request from a ride requestor associated with ride criteria including a pick-up location and a drop-off location. The method includes determining that the ride requestor is a passenger for the vehicle to satisfy the fleet-level objective contingent on modifications to the ride criteria. The method includes providing incentives to the ride requestor contingent on acceptance of the modifications to the ride criteria. The method includes, after receiving the acceptance of the modifications to the ride criteria, modifying the ride criteria in accordance with the route criteria. The method includes instructing the vehicle to transport the ride requestor based on the modified ride criteria so as to fulfill the fleet-level objective.

Abstract: In particular embodiments, a computing system may determine a predicted amount of ride requests for a plurality of collectively-managed vehicles and determine an availability of the collectively-managed vehicles to satisfy the predicted amount of ride requests. Subsequent to determining that the availability fails to satisfy one or more predetermined criteria for servicing the predicted amount of ride requests, the system may determine status information associated with the collectively-managed vehicles and determine, based on at least the status information, one or more minimum services for servicing one or more vehicles among the plurality of collectively-managed vehicles at one or more service centers such that the availability satisfies the one or more predetermined criteria. The system may instruct the one or more vehicles that are to receive the one or more minimum services to travel to the one or more service centers to be serviced.

Abstract: Provided is a method of spatially referencing a plurality of images captured from a plurality of different locations within an indoor space by determining the location from which the plurality of images was captured. The method may include obtaining a plurality of distance-referenced panoramas of an indoor space. The distance-referenced panoramas may each include a plurality of distance-referenced images each captured from one position in the indoor space and at a different azimuth from the other distance-referenced images, a plurality of distance measurements, and orientation indicators each indicative of the azimuth of the corresponding one of the distance-referenced images. The method may further include determining the location of each of the distance-referenced panoramas based on the plurality of distance measurements and the orientation indicators and associating in memory the determined locations with the plurality of distance-referenced images captured from the determined location.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may determine that a first vehicle is unsafe to continue navigating to the drop-off location while the first vehicle is traveling en-route to transport one or more passengers to a drop-off location. Based on this determination, an intermediate area for the one or more passengers to be dropped off by the first vehicle and picked up by a second vehicle is determined. Instructions are then provided to the first vehicle to cause the first vehicle to navigate to the intermediate area. Further, instructions are provided to the second vehicle to navigate at least in proximity to the intermediate area to pick up the one or more passengers, and navigate to the drop-off location after picking up the one or more passengers.

Abstract: In one embodiment, a method includes a computing system receiving information from an autonomous vehicle (AV). Based on the received information, the system may identify a target objective, with an associated target destination, for the AV and determine that the AV is able to transport passengers while furthering the target objective. The system may receive multiple ride requests from ride requestors, respectively. Each of the ride requests is associated with an origination location and a destination location. The system may match the AV with one of the ride requests based on a location of the AV, the target destination of the target objective, and the origination location and destination location associated with the ride request. The system may instruct the AV to perform a transportation task from the origination location to the destination location associated with the ride request, and drive to the target destination after completing the transportation task.

Abstract: In particular embodiments, a computing system may generate a prediction of requests for autonomous vehicles in a fleet of collectively managed autonomous vehicles based on a current condition and a future event, the prediction including a predicted request level and a predicted duration of the request level. The system may receive status information from fleet vehicles and identify a vehicle in need of service. The system may receive status information from service centers and identify a service center to service the vehicle. The system may determine a time at which to service the vehicle at the identified service center based on the generated prediction of requests, schedule the vehicle for service at the identified service center at the determined time, and instruct the vehicle to drive to the service center to be serviced at the determined time. In particular embodiments, the prediction of requests may be generated using machine learning.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may receive respective service center candidacy information from service center computers; determine that an autonomous vehicle requires service work; determine a pool of service centers that are capable of providing the service work for the autonomous vehicle; select, based at least on a reduction in a utilization of at least one resource, a service center from the pool of service centers; and provide, to the autonomous vehicle computing device associated with the autonomous vehicle, location information of the selected service center.

Abstract: In one embodiment, a method includes receiving sensor data from one or more sensors of an autonomous vehicle (AV); determining that a first sensor of the one or more sensors needs recalibration based on the sensor data. The first sensor being of a first sensor type. The method also includes sending a request to a remote management system indicating that one or more of the sensors of the AV need recalibration and a location of the AV; determining the presence of a service vehicle having a calibration target configured to calibrate sensors of the first sensor type; and initiating a calibration routine using the calibration target.

Abstract: In one or more embodiments, one or more systems, methods, and/or processes may receive respective service center candidacy information from service center computers; determine that an autonomous vehicle requires service work; determine a pool of service centers that are capable of providing the service work for the autonomous vehicle; select, based at least on a reduction in a utilization of at least one resource, a service center from the pool of service centers; and provide, to the autonomous vehicle computing device associated with the autonomous vehicle, location information of the selected service center.

Abstract: In one embodiment, a system includes one or more processors and one or more computer-readable non-transitory storage media coupled to one or more of the processors. The one or more computer-readable non-transitory storage media include instructions operable when executed by one or more of the processors to cause the system to perform operations including receiving service-facility data associated with a service facility that includes one or more service regions for servicing autonomous vehicles. Each of the one or more service regions is configured to charge an autonomous vehicle. The service facility data includes location information indicating a location of each of the one or more service regions; and availability information indicating an availability of each of the one or more service regions. The operations also include receiving vehicle data associated with a number of autonomous vehicles. The vehicle data includes a charge level of a respective autonomous vehicle.