Abstract: Electric vehicle battery monitoring systems and methods are disclosed herein. An example method includes displaying a state of charge for a battery of an electric vehicle on a display screen of the electric vehicle, determining a frequency of how often a user views the state of charge, inferring that the user has anxiety over a range for the electric vehicle based on the frequency, and presenting the user with options to extend the state of charge.

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: The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

Abstract: The disclosure is generally directed to systems and methods for providing vehicle payload assistance. An example method executed by processor of a vehicle payload assistance system may include obtaining information about a first laden weight of a vehicle. The processor determines a weight difference between the first laden weight and a payload capacity of the vehicle, and further determines, based on the weight difference, a payload margin available for loading the vehicle. A vehicle payload assistance operation may then be executed that includes detecting a change in the first laden weight due to introduction of an object into the vehicle, obtaining information about a second laden weight of the vehicle after introduction of the object into the vehicle, determining that the second laden weight exceeds the payload margin available for loading the vehicle, and issuing an advisory to reduce the second laden weight by removing the object from the vehicle.

Abstract: The disclosure is generally directed to in-vehicle advertisement systems and methods. An example method executed by processor of a vehicle may include determining an attention availability index of a driver of a vehicle and determining a first presentation duration of a first advertisement based on the attention availability index. In one scenario, the attention availability index of the driver may be determined by applying an inverse relationship to a concentration index associated with driving the vehicle. The first advertisement is presented over the first presentation duration, via an advertisement presentation device in the vehicle. In another scenario, the attention availability index of the driver may be compared to a threshold value. Based on the comparison, a second presentation duration for a second advertisement may be determined and the second advertisement presented via the advertisement presentation device in the vehicle.

Abstract: A system, comprising a computer including a processor and a memory storing instructions executable by the processor to determine a first lateral boundary for movement of a vehicle. The first lateral boundary is parallel to a longitudinal axis of the vehicle and is based on at least a size of the vehicle. Based on at least the size of the vehicle and a detected yaw rate of the vehicle, the instructions include to determine a wind condition at a location. The instructions include to update a distance of the first lateral boundary from the longitudinal axis to obtain an updated first lateral boundary, based on the wind condition.

Abstract: The disclosure generally pertains to systems and methods for providing a personalized advertisement service. In an example method, first information associated with a vehicle can be identified. The first information can include at least a present location of the vehicle, a present speed of the vehicle, and traffic information associated with a present route of the vehicle. Second information associated with a driver of the vehicle can also be identified. An advertisement interaction score can be calculated based at least in part on the first information and the second information. A nature of an advertisement to be displayed at a vehicle infotainment system of the vehicle can be subsequently determined. The nature of the advertisement can comprise a viewable characteristic or a clickable characteristic. The advertisement can then be displayed at the vehicle infotainment system.

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: The disclosure is generally directed to in-vehicle advertisement systems and methods. An example method executed by processor of a vehicle may include determining an attention availability index of a driver of a vehicle and determining a first presentation duration of a first advertisement based on the attention availability index. In one scenario, the attention availability index of the driver may be determined by applying an inverse relationship to a concentration index associated with driving the vehicle. The first advertisement is presented over the first presentation duration, via an advertisement presentation device in the vehicle. In another scenario, the attention availability index of the driver may be compared to a threshold value. Based on the comparison, a second presentation duration for a second advertisement may be determined and the second advertisement presented via the advertisement presentation device in the vehicle.

Abstract: This disclosure describes systems and methods for personalized route prediction. An example method may include receiving, at a first time, first input data associated with a first route traversed by a vehicle. The example method may also include populating a first database with the input data. The example method may also include receiving, at a third time, second input data associated with a second route traversed by the vehicle. The example method may also include comparing the second input data to the first input data included within the first database. The example method may also include determining, based on the comparison, a first cluster including the first data and the second input data or a second cluster including the second input data. The example method may also include populating a second database based on the first cluster or the second cluster.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to identify a first scenario in which a vehicle is operating from a plurality of scenarios, prompt an operator to activate an adaptive cruise control of the vehicle in response to a preference score for the first scenario being above a threshold, refrain from prompting the operator to activate the adaptive cruise control in response to the preference score for the first scenario being below the threshold, and activate the adaptive cruise control in response to receiving an input to activate the adaptive cruise control from the operator. The scenarios indicate at least one characteristic of a road on which the vehicle is traveling. The preference score indicates a preference of the operator for activating the adaptive cruise control in the first scenario.

Abstract: A profile for an occupant is stored. The profile includes a plurality of clusters of sitting positions for the occupant in a seat and classifications of respective clusters as preferred or nonpreferred. Respective clusters are classified as preferred or nonpreferred based on sitting scores for the respective sitting positions in that cluster. A higher sitting score increases a likelihood of the classification being preferred. A series of pressure maps indicating a respective series of sitting positions of the occupant in the seat are received. The pressure maps include a current pressure map. One of the sitting positions is assigned to one of the clusters that is classified as preferred in response to the sitting score of that sitting position being greater than a threshold score. A physical configuration of the seat is adjusted in response to the current sitting position being in one of the clusters that is classified as nonpreferred.

Abstract: The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

Abstract: A system, comprising a computer including a processor and a memory storing instructions executable by the processor to determine a first lateral boundary for movement of a vehicle. The first lateral boundary is parallel to a longitudinal axis of the vehicle and is based on at least a size of the vehicle. Based on at least the size of the vehicle and a detected yaw rate of the vehicle, the instructions include to determine a wind condition at a location. The instructions include to update a distance of the first lateral boundary from the longitudinal axis to obtain an updated first lateral boundary, based on the wind condition.

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: 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: 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: 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.