Abstract: A system comprises a processor that is programmed to define a plurality of vehicle groups based on vehicle specification data and define a plurality of sub-groups for each of the vehicle groups based on environmental data and sensor data received from each of a plurality of vehicles. The processor is programmed to adjust fuel tank leak detection classifiers for the sub-groups based on ground truth data. The ground truth data include, for each of the plurality of vehicles, a leak detection status and a leak test result.

Abstract: This disclosure is generally directed to systems and methods for protecting the health of occupants of a vehicle. In an example method, a sensor in a vehicle sends sensor data to a computer, based on detecting a symptomatic feature that indicates a health status of a first occupant of the vehicle. In one case, the symptomatic feature may be an elevated body temperature that may be symptomatic of a fever. In another case, the detected symptomatic feature may be a sound emitted by the first occupant such as, for example, a cough, a sneeze, or a wheeze. The computer evaluates the sensor data and identifies a health risk posed by the first occupant to a second occupant of the vehicle. The computer may address the health risk, for example, by modifying an air quality inside the vehicle or by instructing the occupants of the vehicle to don masks.

Abstract: Vehicle payment communications systems and methods are disclosed herein. An example method can include identifying a shared payment device, the shared payment device being a connected vehicle, transmitting a shared payment request to the shared payment device, the shared payment device authorizing a shared payment for the payment of a good or service to a merchant, receiving an indication that the shared payment has been authorized and completed in accordance with the shared payment request, and obtaining the good or service from the merchant.

Abstract: A system comprises an image sensor with a field of view of an exterior of a vehicle; a human machine interface (HMI) in the vehicle arranged to display images based on data from the image sensor; and a first computer that includes a processor and a memory. The first computer is programmed to provide data from the image sensor to a machine learning program that outputs a bounding box around an object; cause the bounding box around the object to be displayed via the HMI; and transmit object data including an inputted label identifying the object to a second computer that is remote from the vehicle.

Abstract: An arrival time of a primary vehicle to arrive at a stopping location is predicted based a current path of the primary vehicle. A predicted transit time period of a secondary vehicle to move to the stopping location is received. Upon determining that a current time is a time that is the predicted transit time period subtracted from the arrival time, a message is sent from the primary vehicle to the secondary vehicle instructing the secondary vehicle to move to the stopping location.

Abstract: The disclosure describes systems and methods for determining and adjusting a parking position of a vehicle. In particular, the vehicle may determine a first parking space where the vehicle can move to a second parking space and exit the second parking space in a forward direction.

Abstract: Systems and methods for an in-vehicle entertainment system located in a vehicle include determining that the in-vehicle entertainment system is in operation, determining vehicle information available to the in-vehicle entertainment system, determining user data available to the in-vehicle entertainment system, determining a level of user interaction based on the vehicle information and the user data, and adjusting a minimum advertisement play window prior to permitting a skip to user-chosen content as a function of the level of user interaction. Vehicle information includes traffic, speed, and location. User data includes data related to whether a passenger is present, historical user data, the historical user data identifying past interactions, and user preferences associated with the in-vehicle entertainment system.

Abstract: An identifier for first set of display content on a vehicle display is input to a statistical model that outputs a plurality of probabilities that a user input will select each of a plurality of second set of display contents for display after the first set of display content is displayed. A first probability is identified for a predicted set of display content that is a highest probability in the plurality of probabilities. The plurality of probabilities are provided to at least one of an optimization model and a neural network upon determining an accuracy of the statistical model is below a threshold. Upon receiving, from the at least one of the optimization model and the neural network, a second probability for the predicted set of display content, the display content is selected based on the first and second probabilities. The vehicle display is updated based on the selected set of display content.

Abstract: Methods and systems are provided for learning characteristics of a road segment and using the learning during a subsequent travel on the road segment to preview the road segment and schedule diagnostic routines to increase in-use monitor performance (IUMP) rates for vehicle system diagnostics. In one example, a method may include scheduling a diagnostic routine for an engine sub-system based on the learned characteristics of the road segment, and a variable adjustable based on IUMP rate.

Abstract: A system is disclosed that may comprise: one or more processors of a center node, wherein the center node is a vehicle computer; and memory of the center node, wherein the memory stores instructions executable by the one or more processors, the instructions comprising to: determine a first network comprising the center node and a plurality of member nodes based on a mesh network of the center node and the plurality of member nodes; add at least one virtual node to the first network; and using the first network, exchange cryptographic data between the at least one virtual node, the center node, and the plurality of member nodes.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive a series of pressure maps indicating a respective series of sitting positions of an occupant in a seat, wherein the pressure maps include a current pressure map; update a profile of the occupant based on the pressure maps, wherein the profile includes a plurality of clusters of sitting positions and classifications of the clusters as preferred or nonpreferred, and updating the profile includes sorting one of the sitting positions into one of the clusters that is classified as preferred in response to the occupant remaining in that sitting position for greater than a threshold time; and adjust a physical configuration of the seat in response to the current sitting position being in one of the clusters that is classified as nonpreferred.

Abstract: Example embodiments described herein are generally directed to a navigation system that generates a pedestrian travel path based on various types of data stored in a database, such as, for example, a map, a blueprint, a historical record, a public record, and/or a personal record. In an example embodiment, the data may be obtained by executing a crowdsourcing procedure, where multiple individuals provide various types of information such as, information about an underground walkway, an elevated walkway, an unpaved pedestrian path, weather conditions, handicap-friendly pathways, and handicap-friendly structures. In an example application, a navigation device receives a navigation request that includes a start spot and an end spot for a pedestrian trip. The navigation device evaluates data stored in a database and uses the data to generate a pedestrian travel path that may include an underground walkway, an elevated walkway, an unpaved pedestrian path, and/or an enclosed pedestrian path.

Abstract: The disclosure is generally directed to systems and methods for facilitating travel over a last leg of a journey. In one example embodiment, an unmanned aerial vehicle (UAV) captures an image of an area to be traversed by an individual during the final leg of the journey. The image is evaluated to identify a hindrance that may be encountered by the individual in the area. A pre-emptive action may be taken to address the hindrance before reaching the area. The pre-emptive action, may, for example, include using the UAV and/or a terrestrial robot to assist the individual traverse the area. The assistance may be provided in various ways such as by use of the terrestrial robot to transport the individual and/or a personal item of the individual through the area, and/or by use of the UAV to provide instructions to guide the individual through the area.

Abstract: Opportunistic fueling for car hailing autonomous vehicles are disclosed herein. An example method includes evaluating a trip schedule having one or more destinations for a vehicle, calculating a plurality of potential routes based on the trip schedule with fueling options along a proposed path of travel for the vehicle, applying one or more vehicle fueling constraints, selecting an optimized route from the plurality of potential routes for the vehicle using the one or more vehicle fueling constraints, and completing the trip schedule using the optimized route.

Abstract: A system is disclosed that may comprise: one or more processors of a center node, wherein the center node is a vehicle computer; and memory of the center node, wherein the memory stores instructions executable by the one or more processors, the instructions comprising to: determine a first network comprising the center node and a plurality of member nodes based on a mesh network of the center node and the plurality of member nodes; add at least one virtual node to the first network; and using the first network, exchange cryptographic data between the at least one virtual node, the center node, and the plurality of member nodes.

Abstract: An example method of crowd-sourcing energy consumption data for vehicles includes controlling a vehicle in response to a predicted energy consumption that is continually updated based on a difference between a previous predicted energy consumption and a previous actual base energy consumption. Another example method of routing a vehicle includes changing a route for a vehicle in response to a predicted energy consumption for the vehicle when travelling the route, the predicted energy consumption based on a difference between a previous predicted energy consumption and a previous actual base energy consumption.

Abstract: A computer determines that a rate of travel value for a route segment being traversed by a first vehicle exceeds a predetermined threshold. A maneuver is planned for the first vehicle to depart from the route segment based on collected vehicle operating data from one or more second vehicles previously traversing the route segment. The first vehicle is instructed to execute the maneuver to depart the route segment.

Abstract: Opportunistic fueling for car hailing autonomous vehicles are disclosed herein. An example method includes evaluating a trip schedule having one or more destinations for a vehicle, calculating a plurality of potential routes based on the trip schedule with fueling options along a proposed path of travel for the vehicle, applying one or more vehicle fueling constraints, selecting an optimized route from the plurality of potential routes for the vehicle using the one or more vehicle fueling constraints, and completing the trip schedule using the optimized route.

Abstract: A system comprises a processor that is programmed to define a plurality of vehicle groups based on vehicle specification data and define a plurality of sub-groups for each of the vehicle groups based on environmental data and sensor data received from each of a plurality of vehicles. The processor is programmed to adjust fuel tank leak detection classifiers for the sub-groups based on ground truth data. The ground truth data include, for each of the plurality of vehicles, a leak detection status and a leak test result.

Abstract: A method for identifying vehicle vibration includes receiving signals indicative of a vehicle vibration from one or more vehicle sensors while the vehicle is in operation. The method also includes determining a magnitude of the vehicle vibration at one or more target frequency bands. The method additionally includes determining whether the vehicle vibration is associated with one or more wheels of the vehicle based on the magnitude of the vehicle vibration at the one or more target frequency bands. The method further includes generating a diagnostic recommendation when the vehicle vibration is associated with the one or more wheels of the vehicle.