A system and method for locating nearby attended delivery/pickup locations with a particular item in stock is described. The system receives a request from an individual to purchase a particular item from an on-line retailer. The system receives information associated with attended delivery/pickup locations, including location and inventory information. The system then determines which (if any) attended delivery/pickup locations (e.g., the attended delivery/pickup locations are not the on-line retailer) are near the individual and have the particular item in stock and notifies the individual. In various embodiments, the system enables the user to purchase or reserve the particular item at the particular attended delivery/pickup location.

A system and method for locating nearby attended delivery/pickup locations with a particular item in stock is described. The system receives a request from an individual to purchase a particular item from an on-line retailer. The system receives information associated with attended delivery/pickup locations, including location and inventory information. The system then determines which (if any) attended delivery/pickup locations (e.g., the attended delivery/pickup locations are not the on-line retailer) are near the individual and have the particular item in stock and notifies the individual. In various embodiments, the system enables the user to purchase or reserve the particular item at the particular attended delivery/pickup location.

A managing apparatus for positioning rental vehicles includes a memory storing instructions and a processor configured to execute the instructions to cause the managing apparatus to access model information and location information for a plurality of autonomous vehicles, receive a request including a delivery location and a chosen model for renting, select an autonomous vehicle of the chosen model from among the plurality of autonomous vehicles based on the model information, the location information, and the delivery location, instruct the selected autonomous vehicle to fully-autonomously or semi-autonomously travel to the delivery location, and instruct the selected autonomous vehicle to switch to manual operation mode at the delivery location for manual operation by a vehicle rental customer.

A managing apparatus for positioning rental vehicles includes a memory storing instructions and a processor configured to execute the instructions to cause the managing apparatus to access model information and location information for a plurality of autonomous vehicles, receive a request including a delivery location and a chosen model for renting, select an autonomous vehicle of the chosen model from among the plurality of autonomous vehicles based on the model information, the location information, and the delivery location, instruct the selected autonomous vehicle to fully-autonomously or semi-autonomously travel to the delivery location, and instruct the selected autonomous vehicle to switch to manual operation mode at the delivery location for manual operation by a vehicle rental customer.

Respective initial feature sets are obtained for the nodes of a graph in which the nodes represent instances of entity types and edges represent relationships. Using the initial feature sets and the graph, a graph convolutional model is trained to generate one or more types of predictions. In the model, a representation of a particular node at a particular hidden layer is based on aggregated representations of neighbor nodes, and an embedding produced at a final hidden layer is used as input to a prediction layer. The trained model is stored.

Respective initial feature sets are obtained for the nodes of a graph in which the nodes represent instances of entity types and edges represent relationships. Using the initial feature sets and the graph, a graph convolutional model is trained to generate one or more types of predictions. In the model, a representation of a particular node at a particular hidden layer is based on aggregated representations of neighbor nodes, and an embedding produced at a final hidden layer is used as input to a prediction layer. The trained model is stored.

An autonomous robot vehicle in accordance with aspects of the present disclosure includes a conveyance system and a compartment coupled to the conveyance system. The conveyance system autonomously drives the autonomous robotic vehicle between one or more storage locations and one or more delivery locations. The compartment receives one or more items stored at the one more storage locations. The compartment includes a temperature control module configured to maintain the compartment within a predetermined temperature range to provide temperature control for the one or more items as the conveyance system drives between the one or more storage locations and the one or more delivery locations.

An autonomous robot vehicle in accordance with aspects of the present disclosure includes a conveyance system and a compartment coupled to the conveyance system. The conveyance system autonomously drives the autonomous robotic vehicle between one or more storage locations and one or more delivery locations. The compartment receives one or more items stored at the one more storage locations. The compartment includes a temperature control module configured to maintain the compartment within a predetermined temperature range to provide temperature control for the one or more items as the conveyance system drives between the one or more storage locations and the one or more delivery locations.

Systems and methods are provided for reducing consumer electronic device returns. According to various aspects, a server receives (505) usage data of an electronic communication device by a consumer. The server examines (510) existing usage indicating correlations between various usage factors of additional devices and return incidents of the additional devices, and calculates (515) individual probabilities of return for the various usage factors and a total probability of return for the electronic communication device. In embodiments, if any of the individual probabilities or the total probability meets or exceeds a threshold probability, the server contacts (535) at least one of the electronic communication device or the consumer.

Systems, apparatuses, and methods are provided herein for processing returns. A system for processing returns, comprises a customer profile database, a communication device, and a control circuit. The control circuit being configured to: receive, via the communication device, information on a return item being returned by a first customer associated with a delivery agent, retrieve customer partiality vectors of a plurality of customers associated with the delivery agent from the customer profile database, select a second customer from the plurality of customers based on the partiality vectors of the second customer, and instruct the delivery agent to reroute the return item from the first customer to the second customer.