Abstract: A fleet management system including a transceiver and a processor is disclosed. The transceiver may be configured to receive a first charger location associated with a first charger, a second charger location associated with a second charger, and a current battery State of Charge (SoC) level associated with a vehicle. The processor may obtain the first charger location, the second charge location and the current battery SoC level from the transceiver responsive to obtaining a trigger signal. The processor may further determine a geo-distance between the first and second charger locations, and estimate an expected battery SoC level required by the vehicle to travel from the first charger location to the second charger location based on the geo-distance. The processor may compare the expected and current battery SoC levels, and output a notification when the current battery SoC level may be greater than the expected battery SoC level.

Abstract: 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: An electric vehicle charging recommendation method is disclosed. The method may include obtaining a vehicle information associated with a vehicle, a driver information, and a vehicle trip information. The vehicle information may include a current state of charge (SOC) of a vehicle battery. The method may further include determining a distance to be travelled by the vehicle from a vehicle current location based on the vehicle trip information. The method may further include determining an expected SOC required to travel the distance from the vehicle current location based on the vehicle information, the driver information and the vehicle trip information. The method may additionally include transmitting a recommendation notification to a user device to charge the vehicle battery when the expected SOC may be greater than the current SOC.

Abstract: A vehicle charging management method is disclosed. The method may include obtaining a first input associated with a vehicle. The first input may include a state of charge (SOC) level of a vehicle battery, a distance travelled by the vehicle since last charge, and time since the last charge. The method may further include obtaining a second input associated with historical vehicle battery charging information. Responsive to obtaining the first input and the second input, the method may include determining a vehicle user intent to charge the vehicle battery. The method may further include comparing the vehicle user intent with a threshold value, and transmitting a notification to a communication device when the vehicle user intent is greater than the threshold value.

Abstract: A vehicle charging management method is disclosed. The method may include obtaining a first input associated with a vehicle. The first input may include a state of charge (SOC) level of a vehicle battery, a distance travelled by the vehicle since last charge, and time since the last charge. The method may further include obtaining a second input associated with historical vehicle battery charging information. Responsive to obtaining the first input and the second input, the method may include determining a vehicle user intent to charge the vehicle battery. The method may further include comparing the vehicle user intent with a threshold value, and transmitting a notification to a communication device when the vehicle user intent is greater than the threshold value.

Abstract: Systems and methods for personalized route prediction including receiving, at a first time, first input data associated with a first route; populating a first database with the input data; receiving, at a third time, second input data associated with a second route; comparing the second input data to the first input data included within the first database; 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; populating a second database based on the first cluster or the second cluster; determining, using the first database and at a second time, at least one of: predicted departure data, predicted destination data, and/or predicted route data; and causing, based on the predicted departure data, predicted destination data, and/or predicted route data, to perform an action in association with a vehicle.

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: 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: 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: 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: 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: 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: A method for controlling a vehicle includes identifying a user identity associated with a user riding in the vehicle, determining a destination associated with the user identity, creating a detection zone proximate to the vehicle when the vehicle is localized in a first drop-off location associated with the destination, causing a sensory system to identify a hazard within the detection zone and generate a localization of the hazard, determining that a first probability of realizing a risk associated with the hazard is less than a first probability threshold, and generating a vehicle door actuation that permits the user to exit the vehicle based on the first probability of realizing the risk.

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.