Abstract: A system and method for dynamically adjusting attributes for a network service is described. A computing system can determine a change that is to be implemented to an attribute of the network service. For each of a plurality of computing devices, the computing system can receive information associated with that computing device from a designated application operating on that computing device. The designated application is associated with the network service. The computing system automatically implements the change to at least one but not all of the plurality of computing devices based on the information received from each of the plurality of computing devices.

Abstract: Systems and methods for determining out-of-stock predictions for merchant items and performing intervention actions based on the out-of-stock predictions using machine-learned models. The method includes obtaining feature data including at least (i) aggregations of historical found rate data, (ii) item level metadata, and (iii) merchant signal data into an out-of-stock model. The method includes determining a number of output scores for a number of items. The output scores can be indicative of a likelihood of an item being out-of-stock. The method includes determining a first output score for a first item of the plurality of items satisfies an intervention criterion. The method includes responsive to determining the first output score satisfies the intervention criterion, performing an intervention action.

Abstract: A method includes receiving one or more search terms at a mobile computing device while the mobile computing device is located at a particular location. A search query that includes the one or more search terms and a location history of the mobile computing device is transmitted to a server. The method also includes receiving one or more search results in response to the search query, where the one or more search results include content identified based on a predicted destination of the mobile computing device. An interface identifying the one or more search results is displayed at the mobile computing device.

Abstract: Systems and methods of using sensor data for coordinate prediction are disclosed herein. In some example embodiments, for a place, a computer system accesses corresponding service data comprising pick-up data and drop-off data for requests, and accesses corresponding sensor data indicating at least one path of mobile devices of the requesters of the requests, with the at least one path comprising at least one of a pick-up path ending at the pick-up location indicated by the pick-up data and a drop-off path beginning at the drop-off location indicated by the drop-off data. In some example embodiments, the computer system generates at least one predicted geographic location using the paths indicated by the sensor data, and stores the at least one predicted geographic location in a database in association with an identification of the place.

Abstract: A system can receive location data from a computing device of a requesting user, where the location data indicates a current position of the requesting user. The system can determine a rendezvous location for the requesting user prior to the requesting user transmitting a service request to the network computer system. The system may then transmit data corresponding to the rendezvous location to the computing device of the requesting user. The system may further periodically receive an update request from the computing device of the user, and for each update request, (i) determine a second plurality of transport providers with the predetermined distance or time from the current position of the user, and (ii) based on respective locations of these transport providers, transmit updated map data to the computing device to indicate an updated rendezvous location on the map interface.

Abstract: A computing system can detect, based on data received via the network communication interface, a launch of a service application on a computing device of a user to initiate an application session. During the application session, the system can obtain contextual data corresponding to user interactions with the service application by the user. Based on the contextual data, the system can perform at least one of (i) acquire first additional user data corresponding to the user from one or more local data sources, or (ii) derive second additional user data associated with the contextual data to avoid a network call and reduce network latency. The system may then classify the user in a specified group for providing targeted content.

Abstract: A computing system detects activation of a service application on a computing device of a user and performs a selection process to select a service provider to provide service for the user before receiving a request for service from the computing device of the user. Before receiving the request for service from the computing device of the user, the system transmits service provider information corresponding to the selected service provider to the computing device of the user. Subsequent to performing the selection process, the system receives the request for service, and transmits an invitation for providing service for the user to a provider device of the selected service provider.

Abstract: A key management system can store, in a tag repository, information associating policy tags with column datasets. The system can receive a client request for an encrypted encryption key (EEK) to access a column dataset, where the client request includes a column name for the column dataset. Based on the client request, the system can perform a lookup in the tag repository to identify one or more tags associated with the column dataset and determine whether the client device is authorized to access the column dataset. Based on determining that the client device is authorized to access the column dataset, the system can generate an original encryption key, and generate the EEK using a shared master key, the original encryption key, and at least the column name for the column dataset. The system may then provide the EEK to the client device over the one or more networks.

Abstract: Under the user's instruction, an autonomous vehicle travels to a selected location. The user chooses a place to arrive at the destination address. After the arrival of the autonomous vehicle, it is determined whether the user's or third party's mobile device is still in the vehicle. If the mobile device is still in the vehicle, the vehicle will notify the user or third party in one or more ways to come back and get their mobile device.

Abstract: In one aspect, a system for automatically assigning vehicle identifiers for autonomous vehicles can include a registry server computing system configured to perform operations. The operations can include receiving, at the registry server computing system and from a vehicle computing system onboard an autonomous vehicle, data describing the autonomous vehicle and generating, at the registry server computing system, a vehicle identifier for the autonomous vehicle based on the data describing the autonomous vehicle. The vehicle identifier can be different than and distinct from the data describing the autonomous vehicle. The operations can include associating, at the registry server computing system, the data describing the autonomous vehicle with the vehicle identifier for the autonomous vehicle in a vehicle registry. The vehicle registry can include respective vehicle identifiers associated with a plurality of autonomous vehicles.

Abstract: A computing system establishes a geofence associated with a particular service area. The system monitors a location of a computing device of a driver and detects when the driver enters the geofence. The system places the driver into a queue for the particular service area. The system receives a transport request from a computing device of a requesting user, where the transport request is associated with the particular service area. The system arranges the transport service for the requesting user in accordance with the set of rules by (i) selecting a driver from the queue to service the transport request for the requesting user, and (ii) communicating at least one of: driver information of the selected driver, an estimated time of arrival to a pickup location, or a location of the selected driver to the computing device of the requesting user.

Abstract: Systems and methods for detecting and orchestrating the deployment of software changes. The system can access schema data indicative of a change associated with a first system, wherein executable code associated with the change is executable within a first computing environment. The system can determine a potential impact to a second system. The system can generate one or more computing tasks to notify the second system of the change and an acknowledgment placeholder with a unique identifier associated with the second system. The system can access data indicative of an execution status of the one or more computing tasks. The system can generate an update indicating that the one or more computing tasks have been executed by the second system. The system can transmit to the first system, data acknowledging the potential impact to the second system, and command instructions to deploy the executable code to a second computing environment.

Abstract: A transportation management system generates routing guidance from an origin location to a destination location by modifying edge weights in a graph of a geographic location to penalize difficult immediate maneuvers. Responsive to receiving a routing request, the system identifies a position of a provider device in a base map having edges representing road segments and nodes representing intersections between road segments. A sub-graph is generated for the edges in the base graph located up to a threshold distance from the origin location, and the system modifies the weight of one or more edges in the sub-graph corresponding to a difficult immediate maneuver. When applying a routing algorithm to generate the routing guidance, the system uses the edge weights of the generated sub-graph for a first portion of the routing guidance and the original edge weights of the base graph for a second portion of the routing guidance.

Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: A method for user-initiated end of delivery confirmation. A method and technique comprises causing display of a first interactive element on a user device in response to a vehicle carrying a payload approaching a destination; receiving a first user input comprising a first user interaction with the first interactive element; in response to receiving the first user input, causing a vehicle management component communicatively coupled to the vehicle to enable access to the payload in the vehicle and causing display of a second interactive element on the user device; receiving a second user input from the user device, the second user input comprising a second user interaction with the second interactive element; determining a retrieval status associated with the payload based on the second user interaction; and causing display of a confirmation on the user device based on retrieval status, the confirmation indicating that the payload has been retrieved.

Abstract: A machine learning model for reinforcement learning uses parameterized families of Markov decision processes (MDP) with latent variables. The system uses latent variables to improve ability of models to transfer knowledge and generalize to new tasks. Accordingly, trained machine learning based models are able to work in unseen environments or combinations of conditions/factors that the machine learning model was never trained on. For example, robots or self-driving vehicles based on the machine learning based models are robust to changing goals and are able to adapt to novel reward functions or tasks flexibly while being able to transfer knowledge about environments and agents to new tasks.

Abstract: A network system determines dissimilarities between a digital map and trace data of a road network in an area as service providers and service requestors coordinate service using the road network in the area. To determine dissimilarities the network system can determine a suggested route, determine a predicted route, receive executed trace data, and compare the predicted route data to the executed trace data for the suggested route. The network system may aggregate trace data when determining a dissimilarity. The network system can quantify the differences between traces to determine dissimilarities. Quantifications can include, ratios, bounds, and scores. The network system can determine and alternate route if a dissimilarity indicates that the state of a road segment has changed (e.g., from “open” to “closed”). The network system can modify guidance instructions if a dissimilarity indicates that a guidance instruction is misleading.

Abstract: A network system obtains position information from a plurality of computing devices that are located within a geographic region where a mass-user facility is provided. A congestion level is determined for an area of the geographic region, based at least in part on the position information obtained from the plurality of computing devices. In response to determining that the congestion level exceeds a threshold level, the network system determines a target distribution profile for managing the use of multiple egress points by users within the geographic region to reduce the congestion level. Application content data can be transmitted to individual computing devices to cause corresponding users to use a corresponding of the multiple egress points, in accordance with the target distribution profile.

Abstract: Systems and methods for displaying corresponding content for vehicle services using a distributed set of electronic devices are provided. For example, a computer-implemented method includes obtaining data associated with a vehicle service instance. The vehicle service instance is associated with a request for a vehicle service for a user. The method includes determining, based on the data associated with the vehicle service instance, a first advertisement content item for a display device positioned on an exterior of a vehicle assigned to the vehicle service instance and a second advertisement content item for a user device associated with the vehicle service instance. The method includes communicating data that initiates the display of the first advertisement content item for the display device positioned on the exterior of the vehicle and data that initiates the display of the second advertisement content item for the user device.

Abstract: Computationally implemented methods and systems that are designed for receiving a request for transporting one or more end users towards a destination location; providing a travel plan for facilitating the one or more end users to travel to the destination location from a starting location, the travel plan identifying at least two route legs including at least one transport route leg that calls for at least one transportation vehicle unit to transport the one or more end users over the transport route leg; and directing the at least one transportation vehicle unit to rendezvous with the one or more end users at a rendezvous location in order to transport the one or more end users over the transport route leg. In addition to the foregoing, other aspects are described in the claims, drawings, and text.