Abstract: A computer-implemented method, system, and computer program product for reducing loads of edge servers in an autonomous mobility environment. The load of an edge server, which controls autonomous vehicles located within the edge server's coverage area, is estimated. In response to the estimated load of the edge server exceeding a threshold value, an action to reduce the load of the edge server is implemented by controlling one or more of the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server. Examples of controlling the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server include modifying a movement of the autonomous vehicle, modifying a frequency of sending vehicle data, offloading calculations to be performed in the autonomous vehicle that were previously being performed in the edge server, restricting lane changes, etc.

Abstract: A computer-implemented method, a computer program product, and a computer system for parallel cross validation in collaborative machine learning. A server groups local models into groups. In each group, each local device uses its local data to validate accuracies of the local models and sends a validation result to a group leader or the server. The group leader or the server selects groups whose variances of the accuracies are not below a predetermined variance threshold. In each selected group, the group leader or the server compares an accuracy of each local model with an average value of the accuracies and randomly selects one or more local models whose accuracies do not exceed a predetermined accuracy threshold. The server obtains weight parameters of selected local models and updates the global model based on the weight parameters.

Abstract: A method for calculating traffic flow changes includes detecting a traffic event. The method further includes determining an affected area of the traffic event and determining an investigation area based on the affected area. The method further includes selecting at least one vehicle located within the investigation area and calculating a change in traffic flow due to the traffic event based on a comparison of a predicted traffic flow with a current traffic flow, wherein the current traffic flow is based on information received from the at least one vehicle. The method further includes updating the affected area based on the change in traffic flow and calculating an updated change in traffic flow based on the updated affected area when the updated affected area is larger than a predetermined threshold area.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate locating temporary distribution lanes on a road for transshipment are provided. According to an embodiment, a system can comprise a processor that executes components stored in memory. The computer executable components can comprise a vehicle network component that can determine one or more vehicles for package delivery from a network of connected vehicles based on delivery destination information. The computer executable components can comprise a lane definition component that can define one or more temporary lanes based on predicted travel positions from the delivery destination information for the one or more vehicles. The computer executable components can comprise a transshipment component that can perform transshipment of packages between the one or more vehicles within the one or more temporary lanes.

Abstract: A computer implemented method provides transshipping. A number of processor units identifies destination information for a load for a first transport vehicle having a first destination and a second transport vehicle having a second destination. The number of processor units determines a lane definition for an ad-hoc transport node on a road based on predicted locations for the first transport vehicle bound for the first destination and the second transport vehicle bound for the second destination. The lane definition defines a set of transfer lanes for the ad-hoc transport node. The number of processor units transfers the load between the first transport vehicle and the second transport vehicle in response to the first transport vehicle and the second transport vehicle being within the ad-hoc transport node.

Abstract: In an approach for reducing economic loss due to traffic events, a processor receives a set of transportation operation information from one or more transportation service providers about a traffic event. A processor analyzes the set of transportation operation information to identify an area affected by the traffic event and one or more users affected by the traffic event. A processor gathers a set of information about each user of the one or more users affected by the traffic event. A processor prioritizes the one or more users affected by the traffic event. A processor determines an alternative plan for each user of the one or more users affected by the traffic event based on the set of information and a priority number given to each user. A processor proposes the alternative plan to each user of the one or more users affected by the traffic event.

Abstract: A system, method, and computer program product receive a request for delivery of a package from an origin to a destination with a desired degree of information disclosure using the Physical Internet. A first carrier for a first leg of the delivery is determined based on the origin and an area coverage of the first carrier. The first carrier is not provided destination information as dictated by the desired degree of information disclosure. A candidate list of other carriers for transporting the package in one or more subsequent legs is identified based on the historical performances of each of the other carriers and the desired degree of information disclosure. A final carrier from the candidate list is determined for a final leg of the delivery. The destination information is disclosed to the final carrier.

Abstract: A computer system trains a federated learning model. A federated learning model is distributed to a plurality of computing nodes, each having a set of local training data comprising labeled data samples. Statistical data is received from each computing node that indicates the node's count of data samples for each label, and is analyzed to identify one or more computing nodes having local training data in which a label category is underrepresented beyond a threshold value with respect to data samples. Additional data samples labeled with the underrepresented labels are provided, and the computing nodes perform training. Results of training are received and are processed to generate a trained global model. Embodiments of the present invention further include a method and program product for training a federated learning model in substantially the same manner described above.

Abstract: Provided are a computer program product, system, and method for configuring and controlling an automated vehicle to perform user specified operations. User vehicle control programs are loaded in an unmanned vehicle to control the unmanned vehicle to perform a user specified operation. The loading the user vehicle control programs replaces base vehicle control programs in the unmanned vehicle. There is communication with the unmanned vehicle to execute the user vehicle control programs to control the unmanned vehicle to perform the user specified operation. The base vehicle control programs are loaded into the unmanned vehicle to replace the user vehicle control programs to return control of the unmanned vehicle to a vehicle provider after performing the user specified operation.

Abstract: Computer-implemented methods, systems and computer program products leveraging collection and analysis of anonymized biological data, location data, individual IDs and time data from groups of individuals within a surrounding environment. The anonymized data can be combined with sources of map data and available historical data to help provide context about the surrounding environment of the users and stored for analysis and decision-making that physically impacts and alters the surrounding environment. At periodic or sporadic intervals, the collected data is extracted and analyzed. Based on the analysis of the anonymized data, physical changes are dynamically implemented within the physical environment, including remotely altering the physical environment by instructing changes to surrounding environment over a computer network such as modifying one or more settings of IoT devices positioned within the surrounding environment analyzed.

Abstract: The method provides for one or more processors to receive traffic information and passing vehicle information associated with a portion of a roadway in which a passing vehicle approaches and travels through the portion of the roadway. The one or more processors predict travel positions of passing vehicles, based on the traffic information and passing vehicle information. The one or more processors determine an impassible space within an existing lane of the roadway and create virtual lane definitions based on the predicting and the traffic information, in which the lane definitions include an optimum number of lanes, a width of respective lanes, and a lane type, and the one or more processors transmit the lane definitions to the passing vehicles based on a correspondence between a type and width of a respective vehicle and the type and width of respective lane definitions.

Abstract: In an approach for reducing economic loss due to traffic events, a processor receives a set of transportation operation information from one or more transportation service providers about a traffic event. A processor analyzes the set of transportation operation information to identify an area affected by the traffic event and one or more users affected by the traffic event. A processor gathers a set of information about each user of the one or more users affected by the traffic event. A processor prioritizes the one or more users affected by the traffic event. A processor determines an alternative plan for each user of the one or more users affected by the traffic event based on the set of information and a priority number given to each user. A processor proposes the alternative plan to each user of the one or more users affected by the traffic event.

Abstract: An ability of a power transmission device to transfer electric charge in a power-transmission area at a particular point in time is identified. The ability comprises a threshold number of vehicles to which the power-transmission device can transfer electric charge with at least a threshold efficiency. A predicted number of electric vehicles that are likely to be requesting electric charge within the power-transmission area at the particular point in time is calculated. The number of electric vehicles that are likely to be requesting electric charge within the power-transmission area at the particular point in time is adjusted based on a determination that the predicted number of vehicles is not bound by the threshold number of vehicles.

Abstract: Computer hardware and/or software configured to determine a plurality of parking spaces on a roadway within a pre-defined geographic location, wherein the plurality of parking spaces are available parking spaces on a side of the roadway, determine a plurality of autonomous vehicles to be parked within the pre-defined geographic location, allocate a selected parking space from the plurality of parking spaces to an autonomous vehicle of the plurality of autonomous vehicles, and transmit parking space information to the autonomous vehicle, wherein the parking space information includes the selected parking space.

Abstract: In an approach for generating the most optimal support execution method, a processor receives a shopping support request from a user requesting at least one product be purchased and delivered to the user while the user travels along a scheduled travel route via a public or private transportation method. A processor identifies a plurality of delivery places and a plurality of delivery times. A processor determines at least one shopper candidate who can purchase and deliver the at least one product. A processor presents, to the at least one shopper candidate, a list comprised of optimal support execution methods. Responsive to receiving an acceptance of the shopping support request, a processor sends a support task to at least one shopper. A processor enables the at least one shopper to execute the shopping support request. A processor dynamically updates one or more details of the support task.

Abstract: Provided are techniques for organizing a temporary device group for collaborative computing. A list of functions for each of a plurality of devices are stored. A determination is made to form a device group including a receiver device from the plurality of devices, where the receiver device will perform one of the functions. An individual function usage score is generated. In response to the individual function usage score exceeding a device threshold, a request to form a device group is sent to the receiver device. In response to receiving an indication of acceptance to form the device group from the receiving device, the device group is formed for a temporary period, where functions and data are shared in the device group.

Abstract: The method provides for one or more processors to receive traffic information and passing vehicle information associated with a portion of a roadway in which a passing vehicle approaches and travels through the portion of the roadway. The one or more processors predict travel positions of passing vehicles, based on the traffic information and passing vehicle information. The one or more processors determine an impassible space within an existing lane of the roadway and create virtual lane definitions based on the predicting and the traffic information, in which the lane definitions include an optimum number of lanes, a width of respective lanes, and a lane type, and the one or more processors transmit the lane definitions to the passing vehicles based on a correspondence between a type and width of a respective vehicle and the type and width of respective lane definitions.

Abstract: Provided are techniques for a Generative Adversarial Networks (GANs) based identification of an edge server. At a first edge server, a global discriminator that has been trained with common data is received. It is determined that area data is imbalanced using the global discriminator. A local discriminator is trained with the area data to generate a first result. An exchanged local discriminator from a second edge server is trained with the area data to generate a second result. The first result and the second result indicate that the first edge server and the second edge server are proximate. The first edge server and the second edge server are added to an edge server group list. At least one of an application model and a configuration of an application is updated from one of the first edge server and the second edge server, and the application is executed.

Abstract: Provided are a computer program product, system, and method for configuring and controlling an automated vehicle to perform user specified operations. User vehicle control programs are loaded in an unmanned vehicle to control the unmanned vehicle to perform a user specified operation. The loading the user vehicle control programs replaces base vehicle control programs in the unmanned vehicle. There is communication with the unmanned vehicle to execute the user vehicle control programs to control the unmanned vehicle to perform the user specified operation. The base vehicle control programs are loaded into the unmanned vehicle to replace the user vehicle control programs to return control of the unmanned vehicle to a vehicle provider after performing the user specified operation.

Abstract: A computer system trains a federated learning model. A federated learning model is distributed to a plurality of computing nodes, each having a set of local training data comprising labeled data samples. Statistical data is received from each computing node that indicates the node's count of data samples for each label, and is analyzed to identify one or more computing nodes having local training data in which a label category is underrepresented beyond a threshold value with respect to data samples. Additional data samples labeled with the underrepresented labels are provided, and the computing nodes perform training. Results of training are received and are processed to generate a trained global model. Embodiments of the present invention further include a method and program product for training a federated learning model in substantially the same manner described above.