Abstract: A method comprises determining a vectorized representation of positions of road agents and road geometry based on sensor data from a vehicle, inputting the vectorized representation of the positions of the road agents and the road geometry into a trained transformer network, predicting one or more road agent trajectories at one or more future time steps based on an output of the transformer network, predicting an acceleration of the vehicle at the one or more future time steps based on the predicted one or more road agent trajectories at the one or more future time steps, and causing the vehicle to perform the predicted acceleration at the one or more future time steps.

Abstract: An approach is provided for linearizing a network of features for machine learning tasks. The approach involves, for instance, receiving a graph representation of a network of a plurality of features. For example, a plurality of vertices of the graph representation, an edge connecting two vertices of the plurality of vertices, or a combination thereof respectively represents the plurality of features. The approach also involves determining a linear order of the plurality of features based on a selected criterion. The approach further involves generating a vector representation of the plurality of features based on the linear order. The approach further involves using the vector representation as an input, an output, or a combination thereof of a machine learning model.

Abstract: A method comprises receiving, at a vehicle system of a vehicle, sensor data from one or more sensors; detecting an object based on the sensor data; determining whether a dynamic map maintained by a remote computing device includes the detected object; upon determination that the dynamic map includes the detected object, determining a remaining time-to-live associated with the detected object based on data associated with the dynamic map; and transmitting data about the detected object to the remote computing device if the determined remaining time-to-live associated with the detected object is less than a predetermined threshold time.

Abstract: Systems and methods for unifying business records data from different database sources into a common format in the same repository are disclosed. In one embodiment, a process includes receiving, by an integration platform system, a first set of business records data from a customer records system, where the business records data includes records in a first format, identifying a first transformation rule corresponding to the first format using the integration platform system, where the first transformation rule includes information for converting data from the first format to a unified format, converting each record in the first set of business records from the first format to the unified format by the integration platform system using the first transformation rule, and storing the first set of converted records in the unified format in a business records database.

Abstract: Methods, vehicles, and systems described herein generate alerts based on a generated macro state level indicative of a traffic hazard risk in view of a set of parameters which may lead driver to make various sub-conscious decisions. The set of parameters can include at least one of a vehicle parameter, driver state parameter, or external parameter.

Abstract: Systems and methods for protecting a vehicle at an intersection are disclosed herein. One embodiment detects that the vehicle is stopped at the intersection at one of a first position and a second position; detects that a driver of the vehicle is pressing on an accelerator pedal of the vehicle; delays acceleration of the vehicle automatically by a first predetermined period, when the vehicle has been detected at the first position; and delays acceleration of the vehicle automatically by a second predetermined period, when the vehicle has been detected at the second position. Delaying acceleration of the vehicle automatically prevents the vehicle from being struck by a cross-traffic vehicle that has proceeded through the intersection against a first traffic signal in a red-light state.

Abstract: There is provided a method for a session audit in a communication system having a first plane and a second plane. The method can be employed in a case in which the first plane is a control plane and the second plane is a user plane, or a case in which the first plane is a user plane and the second plane is a control plane. The first plane performs operations of (1) sending to the second plane, an association update request that contains a first vendor-specific information element (IE) having (a) a bit set to indicate a desire for a single control plane (CP) fully-qualified session identification (CP F-SEID), and (b) a CP F-SEID, and (2) receiving from the second plane, an association update response that contains a second vendor-specific IE having (a) the CP F-SEID, and (b) a mapped user plane (UP) fully-qualified session identification (UP F-SEID).

Abstract: Driver classification systems and methods are disclosed herein. The driver classification method includes collecting first vehicle driving data from a first vehicle, processing the first vehicle driving data using a driver classification learning model including a machine learning algorithm at one of an edge server and the first vehicle to assign a driver classification to the first vehicle, updating the driver classification learning model based on additional driver classification learning models received from a plurality of additional vehicles, sending the driver classification to an insurance provider, receiving an insurance rate for the first vehicle from the insurance provider based on the driver classification of the first vehicle, and providing the insurance rate to the first vehicle.

Abstract: A Shared Cell (SC) Controller uses deployment information, radio resource utilization measurements, cell load measurements, signal quality measurement, operator's policies and radio capabilities to make decisions on system configuration, re-configuration, and channel allocation related to the Shared Cell groups. The SC Controller may also use artificial intelligence/machine learning to predict future system state when making decisions on system configuration and channel allocation. The SC Controller can be implemented in the context of using a CBRS system, the ORAN architecture, and the Shared Cell group of Radio Units (RUs). SC Controller can be implemented as part of the Non-Real Time Radio Intelligent Controller (Non-RT RIC). The SC Controller interfaces with the Citizens Broadband Radio Service Device (CBSD) Controller, and the SC Controller sends the Shared Cell group information to the O-RU Controller so that the O-RU Controller can configure the radio components.

Abstract: A hybrid deterministic override to cloud based probabilistic advanced driver assistance systems. Under default driving conditions, an ego vehicle is controlled by a probabilistic controller in a cloud. An overall gap between the ego vehicle and a leading vehicle is divided into an emergency collision gap and a driver specified gap. The vehicle sensors monitor the overall gap. When the gap between the ego vehicle and the leading vehicle is less than or equal to the emergency collision gap, a deterministic controller of the ego vehicle overrides the cloud based probabilistic controller to control the braking and acceleration of the ego vehicle.

Abstract: Systems and methods for personalizing adaptive cruise control in a vehicle are disclosed herein. One embodiment collects vehicle-following-behavior data associated with a particular driver; trains a Gaussian Process (GP) Regression model using the collected vehicle-following-behavior data to produce a set of adaptive-cruise-control (ACC) parameters pertaining to the particular driver, the set of ACC parameters modeling learned vehicle-following behavior of the particular driver; generates an acceleration command for the vehicle based, at least in part, on the set of ACC parameters; applies a predictive safety filter to the acceleration command to produce a certified acceleration command that has been vetted for safety; and controls acceleration of the vehicle automatically in accordance with the certified acceleration command to regulate a following distance between a lead vehicle and the vehicle in accordance with the learned vehicle-following behavior of the particular driver.

Abstract: A vehicle includes a controller programed to: collect a set of data related to a driver of the vehicle; predict a driving setting for the driver using the set of data and an initial student-T process (STP) machine learning (ML) model; generate an updated STP ML model based on the prediction of the driving setting as to the set of vehicle data; transmit incremental learning related to the updated STP ML model to a server; and receive, from the server, a personalized driving setting for the driver output from a cloud STP ML model trained by the incremental learning.

Abstract: Systems, methods, and other embodiments described herein relate to generating a notification about a risk of a target vehicle toppling over due to wind. In one embodiment, a method includes determining a wind force of the wind at a location of the target vehicle and determining one or more characteristics of the target vehicle. The method includes determining whether there is a risk of the target vehicle toppling over based on the wind force of the wind and the one or more characteristics of the target vehicle. The method includes generating a notification about the risk.

Abstract: Systems, methods, and computer program products that are configured to identify or otherwise detect the presence of bacteria, classify the identified or detected bacteria, and also predict the growth of the classified bacteria on various touchable surfaces within a vehicle passenger cabin or compartment. Such systems, methods, and computer program products are configured to identify/detect, classify, and predict the presence and/or growth of bacteria, and transmit one or more alerts, warnings, and/or reports to vehicle owners, service providers, and/or occupants based on the identification/detection, classification, and prediction.

Abstract: Systems, methods, and devices suspend and establish wireless communications connections. Methods include determining a wireless communications device should be transitioned to operate in a first mode of operation, and transitioning first logic of the wireless communications device to operate in the first mode of operation using second logic of the wireless communications device, the first logic implementing a host stack of a Bluetooth protocol, the second logic implementing a controller stack of the Bluetooth protocol, the transitioning of the first logic to operate in the first mode of operation including disconnecting a communications connection.

Abstract: Responsive to a user instruction or a security breach occurring in an enterprise computing environment, an emergency shutdown and restore module is adapted to obtain and evaluate an identity population definition to determine a population of identities (e.g., a forensic team) associated with accounts distributed across applications in the enterprise computing environment. The emergency shutdown and restore module is further adapted to determine source systems of such accounts and communicate with those source systems via source-specific connectors. The emergency shutdown and restore module can respectively request the source systems to shut down access to the applications by the accounts associated with the population of identities, or to exclude the accounts associated with the population of identities in shutting down access to the applications.

Abstract: System, methods, and other embodiments described herein relate to reducing audible distractions for a driver of a vehicle. In one embodiment, a method includes obtaining audio data based on sound detected inside the vehicle, identifying an audio event based on the audio data, determining a distraction rating for the audio event, the distraction rating indicating an estimated level of distraction caused by the audio event, and generating an alert when the distraction rating exceeds a threshold.

Abstract: A warm mission-mode reset may be performed in a portable computing device. Assertion of a signal indicating an error condition may be detected. In response to detection of the signal indicating an error condition, a signal indicating a request to preserve memory contents may be provided to a DRAM subsystem. Then, in response to a signal acknowledging the DRAM subsystem is preserving the memory contents, a system reset signal may be asserted.

Abstract: A method for time sensitive network (TSN) operation includes: in the case of data traffic stoppage in a communication channel of TSN due to at least one of down time of a user plane (UP) connection and a reset of the UP connection, performing the following: generating, by a user plane function (UPF), an audit report about the at least one of the down time and the reset; sending, by the UPF, the audit report to a first element in control plane (CP), without waiting for communication from the CP; and determining, by one of the first element or a second element in the CP, survival time of the communication channel. The audit report is sent along with a report type indicating the down time of the UP connection due to connection fluctuation or a switch-over of the UP connection from a primary UPF to a back-up UPF.

Abstract: A method for rideshare personalization may include identifying one or more unmet needs among a set of needs of a user during a ride of a vehicle based on data from a sensor of the vehicle, updating a user profile of the user to include the one or more unmet needs in association with a set of contextual data related to the ride, and providing services associated with the one or more unmet needs to the user during another ride based on the updated user profile and the set of contextual data related to the another ride.