Abstract: In-vehicle advertisement presentation systems and methods are disclosed herein. An example method includes determining vehicle information for a trip, the vehicle information including any one or more of a current vehicle location, a vehicle speed, a drive mode, and/or traffic information, determining user information, the user information including any one or more of a route prediction for the trip, a speed prediction for the trip, and/or a destination, determining user preferences for advertisements from any one or more of audio signals within the vehicle and/or historical user data, selecting a number of the advertisements to present to the user during the trip, and providing the advertisements to the user during the trip through a human-machine interface (HMI) of the vehicle.

Abstract: Recommendation of off-beat locations as destinations for vehicles is provided. Off-beat locations for a location of a vehicle are identified by a server. Each off-beat location is associated with a corresponding popularity score, the popularity score indicating a relative level of occupancy of the off-beat location. The off-beat locations are filtered by the server based on at least one threshold level of popularity score. The off-beat locations are recommended from the server to the vehicle as those that meet the at least one threshold level of popularity score.

Abstract: A vehicle may determine that erratic vehicle behavior has been sensed, based on comparison of a sensed vehicle behavioral characteristic at a given location compared to a predefined expected value of the characteristic. The vehicle may further determine whether an environmental anomaly has been detected in association with the given location and classify the sensed erratic behavior based on whether the environmental anomaly was detected. Responsive to classifying the behavior as erratic based on determining no environmental anomaly was detected, the vehicle may report the erratic behavior to a remote server, along with the given location. The remote server may receive a plurality of such reports for a given location and update a classification of the behavior based on data indicated in the plurality of reports.

Abstract: A puddle light system projects content-bearing images onto a ground surface adjacent a vehicle using a puddle light projector unit having a multicolor light source configured to project the content-bearing images using at least one selected color from a plurality of available colors. An image sensor directed at the ground surface and mounted on the vehicle is configured to capture colored images. A controller is configured to (A) construct one of the content-bearing images as an image representation with an illumination region to be projected onto the ground, (B) analyze a first colored image of the ground surface with the light source deactivated to identify a dominant surface color, (C) select a complementary color relative to the dominant surface color, (D) colorize the illumination region using the selected complementary color, and (E) command the puddle light projector unit to project the image representation using the colorized illumination region.

Abstract: A vehicle may determine that erratic vehicle behavior has been sensed, based on comparison of a sensed vehicle behavioral characteristic at a given location compared to a predefined expected value of the characteristic. The vehicle may further determine whether an environmental anomaly has been detected in association with the given location and classify the sensed erratic behavior based on whether the environmental anomaly was detected. Responsive to classifying the behavior as erratic based on determining no environmental anomaly was detected, the vehicle may report the erratic behavior to a remote server, along with the given location. The remote server may receive a plurality of such reports for a given location and update a classification of the behavior based on data indicated in the plurality of reports.

Abstract: A vehicle may be configured to detect an object within an interior of the vehicle using a vehicle sensor. The vehicle may further determine whether the object should be removed, based on a determined object value, such as may be determined by comparison of an object characteristic to a database of objects. Also, responsive to determining the object should be removed, the vehicle may schedule removal at an automated object-removal center. The vehicle may also wirelessly notify the object-removal center of vehicle arrival when the vehicle arrives at the object-removal center, including sending identification of the object, receiving indication from the object-removal center that the object has been removed, and confirming removal of the object by attempting to detect the object using the vehicle sensor, the confirmation occurring based on non-detection of the object by the vehicle that originally detected the object and requested removal.

Abstract: A system includes a processor configured to receive a set of user attribute preferences for a trip. The processor is also configured to determine a plurality of trip routes, the routes having variance in a value for at least one user attribute preference as compared to other of the routes. The processor is further configured to present the plurality of routes in a selectable manner, including displaying an attribute value associated with each route and implement navigation for a selected route.

Abstract: Parameters of clusters of a context-encoded model are updated, per frequency estimation of an aspect of calls to contacts with respect to unique combinations of contextual data of calls matching the respective clusters. The clusters are weighted according to relevance of the unique combinations of contextual data to current contextual information. First probabilities of calling individual contacts are determined according to the current contextual information and one or more inferences between calls determined from the clusters as weighted. Second probabilities of calling each of the plurality of contacts are determined according to a set of rules defining prioritizations for contacts based on external factors. Third probabilities of calling each of the plurality of contacts are determined according to calling patterns of other of the plurality of contacts. The first, second, and third sets of weights are combined to determine final predictions for predicted probabilities to call each of the contacts.

Abstract: A server includes a memory configured to store a vehicle feature usage pattern and data associated with a trip; and processor, programmed to responsive to receiving a vehicle selection request for a user, predict a driving condition of the vehicle used by the user during the trip; calculate a usage score for each of a plurality of predefined vehicle safety features based on the vehicle feature usage pattern of the user and the driving condition as predicted; and select, from a plurality of vehicles, one or more vehicles as candidate vehicles based on the usage score as calculated.

Abstract: A first controller receives a diagnostic recommendation from a cloud server. A second controller, in communication with the first controller over a vehicle bus, responsive to occurrence of a vehicle condition triggering execution of an on-board diagnostic (OBD) monitor, suspends the execution of the OBD monitor while the vehicle is within a region specified by the diagnostic recommendation. Locations in diagnostic result data are correlated to identify clusters of locations that include at least a predetermined number of executions of an on-board diagnostic (OBD) monitor. Responsive to a predicted probability of success of execution of the OBD monitor for one of the clusters of locations computed using the diagnostic result data being below an enablement threshold, a message is sent to a vehicle suspending further executions of the OBD monitor at the location.

Abstract: Multiple display infotainment systems in vehicles provide various options for drivers and passengers to interact with elements on the multiple displays. Techniques include accessing historical driver information that includes previous or typical driver preferences and actions while operating the vehicle. Driving context information and driver state information are received describing the conditions in and around the vehicle. When a signal indicates that an interactive element should be presented to the driver or a passenger, an adaptive rule-based system uses the contextual information and previous history to determine a score for each interaction element. The score and they type of interaction required by the element are then used to determine a location on the multiple displays for presenting the interactive element.

Abstract: A vehicle includes a controller, programmed to responsive to user input to pick up an item at a shop, calculate an estimated time of arrival (ETA) to the shop and a predicted preparation time for the item by the shop; and responsive to a current time being within a grace period to the preparation time before the ETA, place an order for the item.

Abstract: A memory stores a probability map including information indicative of probabilities of a vehicle being used during each of a plurality of segments of a time period. A processor of the vehicle is programmed to schedule a time to install a software update utilizing the probability map and an expected downtime required for the installation, and to install the software update at the scheduled time responsive to confirming the vehicle is not in use.

Abstract: A vehicle may be configured to detect an object within an interior of the vehicle using a vehicle sensor. The vehicle may further determine whether the object should be removed, based on a determined object value, such as may be determined by comparison of an object characteristic to a database of objects. Also, responsive to determining the object should be removed, the vehicle may schedule removal at an automated object-removal center. The vehicle may also wirelessly notify the object-removal center of vehicle arrival when the vehicle arrives at the object-removal center, including sending identification of the object, receiving indication from the object-removal center that the object has been removed, and confirming removal of the object by attempting to detect the object using the vehicle sensor, the confirmation occurring based on non-detection of the object by the vehicle that originally detected the object and requested removal.

Abstract: A vehicle includes a controller programmed to identify tag phrases for locations that express a relationship between the location and a learned location tag. The tag phrases are based on words and word sequences learned from prior selections and inputs of a user. The controller is programmed to communicate the tag phrases to the user and provide trip assistance based on a selected tag phrase chosen by the user. The locations and tag phrases are accessible to devices such that locations are identified with common tag phrases on each of the devices.

Abstract: A vehicle may be configured to detect an object within an interior of the vehicle using a vehicle sensor. The vehicle may further determine whether the object should be removed, based on a determined object value, such as may be determined by comparison of an object characteristic to a database of objects. Also, responsive to determining the object should be removed, the vehicle may schedule removal at an automated object-removal center. The vehicle may also wirelessly notify the object-removal center of vehicle arrival when the vehicle arrives at the object-removal center, including sending identification of the object, receiving indication from the object-removal center that the object has been removed, and confirming removal of the object by attempting to detect the object using the vehicle sensor, the confirmation occurring based on non-detection of the object by the vehicle that originally detected the object and requested removal.

Abstract: A memory stores call records to a plurality of contacts. A processor is programmed to determine probabilities of calling contacts according to current contextual information and call inferences determined from clusters of a context-encoded model created from the call records, each cluster corresponding to a unique combination of ranges of values of the contextual information; and identify the most likely next contact to call as the one of the plurality of contacts having a highest of the probabilities.

Abstract: A server includes a memory configured to store a vehicle feature usage pattern and data associated with a trip; and processor, programmed to responsive to receiving a vehicle selection request for a user, predict a driving condition of the vehicle used by the user during the trip; calculate a usage score for each of a plurality of predefined vehicle safety features based on the vehicle feature usage pattern of the user and the driving condition as predicted; and select, from a plurality of vehicles, one or more vehicles as candidate vehicles based on the usage score as calculated.

Abstract: A first controller receives a diagnostic recommendation from a cloud server. A second controller, in communication with the first controller over a vehicle bus, responsive to occurrence of a vehicle condition triggering execution of an on-board diagnostic (OBD) monitor, suspends the execution of the OBD monitor while the vehicle is within a region specified by the diagnostic recommendation. Locations in diagnostic result data are correlated to identify clusters of locations that include at least a predetermined number of executions of an on-board diagnostic (OBD) monitor. Responsive to a predicted probability of success of execution of the OBD monitor for one of the clusters of locations computed using the diagnostic result data being below an enablement threshold, a message is sent to a vehicle suspending further executions of the OBD monitor at the location.

Abstract: A vehicle may be configured to detect an object within an interior of the vehicle using a vehicle sensor. The vehicle may further determine whether the object should be removed, based on a determined object value, such as may be determined by comparison of an object characteristic to a database of objects. Also, responsive to determining the object should be removed, the vehicle may schedule removal at an automated object-removal center. The vehicle may also wirelessly notify the object-removal center of vehicle arrival when the vehicle arrives at the object-removal center, including sending identification of the object, receiving indication from the object-removal center that the object has been removed, and confirming removal of the object by attempting to detect the object using the vehicle sensor, the confirmation occurring based on non-detection of the object by the vehicle that originally detected the object and requested removal.