Abstract: Disclosed are systems and methods for projecting virtual parking lines in alignment with actual parking lines to facilitate parking within a parking stall defined by the actual parking lines to prevent unnecessary damage to vehicles in an area where the actual parking lines may not exist or be visible. The system identifies the location of the actual parking lines within a defined parking area based on previously recorded actual parking line data as well as localization of the vehicle within the defined parking area relative to the nearby landmarks. Virtual parking lines are generated that correspond with the location of the actual parking lines and are projected in alignment with the actual parking lines to facilitate parking.

Abstract: The disclosure generally pertains to systems and methods to predict a vehicle preference of a customer of a rental vehicle agency. An example method to do so involves a computer executing a prediction procedure to obtain and evaluate information associated with a customer. The information can include vehicle ownership history and/or monitoring data obtained from vehicles used by the customer (a personal vehicle, a taxi, and/or a ride share service vehicle, for example). The information may be evaluated by the computer to determine a personal profile of the customer. The personal profile can include items such as physical attributes of the customer, family size, driving characteristics, and/or past vehicle ownership. The personal profile of the customer may then be used by the computer to predict a type of vehicle preferred by the customer and to select, from a vehicle fleet, a vehicle that matches the preferred type of vehicle.

Abstract: While operating a vehicle, a candidate marker is detected via first image data from a first image sensor. Upon failing to identify the candidate marker, vehicle exterior lighting is actuated to illuminate the candidate marker. Then the candidate marker is determined to be one of a real marker or a projected marker based on determining whether the candidate marker is detected via second image data from the first image sensor. Upon determining the candidate marker is the real marker, the vehicle is operated based on the real marker.

Abstract: A server includes a processor, programmed to receive a vehicle location from a vehicle, receive a weather condition of the vehicle location from a cloud server, responsive to receiving a calendar of a user including an event, calculate a departure time based on the vehicle location and a location of the event, responsive to receiving a desired cabin temperature of the user from a mobile device, calculate a minimum time for the vehicle to reach the desired cabin temperature based on the weather condition, calculate a vehicle start time using the departure time and the minimum time, and send an instruction to the vehicle to start at the vehicle start time.

Abstract: A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to access sensor data of a first sensor of a vehicle while an adaptive cruise control feature of the vehicle is active, detect, based on the sensor data of the first sensor, a stationary object located along a path of travel of the vehicle, wherein the stationary object is located outside of a range of a second sensor of the vehicle, determine a presence of an intersection within a threshold distance of the stationary object that is along the path of travel of the vehicle, and responsive to a determination that the stationary object is a stopped vehicle of the intersection, adjust, by the adaptive cruise control feature, the speed of the vehicle.

Abstract: This disclosure is generally directed to systems and methods related to providing advice to a driver of a vehicle involved in a traffic accident. In an example embodiment, a sensor generates a sensor signal based on detecting a traffic accident involving the vehicle in which the sensor is mounted. A computer evaluates the sensor signal and identifies various actions to be performed in conformance with legal and/or insurance requirements applicable to the site of the traffic accident. The legal and/or insurance requirements can vary from one site to another (state to state, for example). The computer may carry out some of the actions automatically and may provide an advisory to the driver of the vehicle to carry out some other actions, such as to exit or stay in the vehicle and to move or not to move the vehicle.

Abstract: A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to monitor a position of a vehicle while an adaptive cruise control feature of the vehicle is set to operate in a standard operation mode, identify, based on the position of the vehicle and on visibility zone information, a limited visibility zone in a route of travel of the vehicle, and cause the adaptive cruise control feature to operate in a modified operation mode while the vehicle is in the limited visibility zone, wherein during operation in the modified operation mode, the adaptive cruise control feature operates in accordance with one or more modified operating parameters.

Abstract: Devices, systems, and methods for boat launching and loading detection and management are disclosed herein. A method may include receiving, by a first device, data associated with operation of a vehicle. The method may include determining, based on the data, that the operation of the vehicle includes at least one of launching a boat into water using the vehicle or loading the boat onto the vehicle. The method may include generating map data indicative of a location associated with the operation of the vehicle. The method may include sending the map data to a second device for presentation.

Abstract: Methods and systems are provided for a start/stop feature. In one example, a method includes adjusting start/stop conditions in response to a vehicle operator customizing start/stop conditions. The vehicle operator customizes start/stop conditions for a plurality of different driving conditions.

Abstract: Systems and methods for re-simulating vehicle ownership are disclosed herein. An example method can include determining route data and vehicle wear and tear data for a route traveled by a first vehicle, determining a cost of the route based on the route data and the vehicle wear and tear data, re-simulating the route data and the vehicle wear and tear data for the route traveled by a second vehicle and determining the cost of the route for the second vehicle, and displaying a comparison of the cost of the route for the first vehicle and the second vehicle.

Abstract: Systems and methods for navigation and logistics management are disclosed herein. An example method can include determining route data for a route traveled by a vehicle. The route data being defined by any one or more of road condition, traffic, fuel consumption, and trip length. Determining vehicle wear and tear data. The vehicle wear and tear data being adjusted based on the route data. Determining a cost of the route based on the route data, the vehicle wear and tear data, and vehicle depreciation. Selecting a remediating action for the vehicle based on the cost of the route. The remediating action when implemented reduces an ownership cost of the vehicle relative to a baseline or expected cost of ownership.

Abstract: A parking space can be identified. A lateral clearance can be identified when a vehicle is parked in the parking space based on identifying a first door of the vehicle to be provided the lateral clearance when the vehicle is parked. A parking position of the vehicle in the parking space can be determined, including a parking bias angle ? between a vehicle longitudinal axis and a parking space longitudinal center axis, and a lateral offset of the vehicle with respect to the parking space longitudinal center axis, based on dimensions of the parking space and the lateral clearance.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive operating data including occupant data indicating one or more occupant actions to operate a vehicle and location data specifying a location of a vehicle during collection of the occupant data, assign the operating data to a respective set in a plurality of sets, each set including operating data collected during a different specified period of time from other sets, input the plurality of sets to a machine learning program trained to output an identification of a hazard at a specified location, the hazard being a roadway condition or an obstacle that changes operation of the vehicle from a default operation, output the hazard at the specified location from the machine learning program, and send a message to a vehicle including the hazard at the specified location.

Abstract: A system for a vehicle includes a memory configured to store modeling parameters, generated using an algorithm that assigns relevance scores to features, that specify information indicative of how configuration data including information indicative of use of features of the vehicle classifies which user is currently using the vehicle. The system also includes a processor programmed to monitor the vehicle for the configuration data, identify a most likely user profile using the modeling parameters according to the configuration data, and apply settings of the user profile to the vehicle.

Abstract: Augmented reality displays for locating vehicles are disclosed herein. An example method includes determining a current location of a mobile device associated with a user, determining a current location of a vehicle, and generating augmented reality view data that includes a first arrow that identifies a path of travel for the ridehail user towards the vehicle. The path of travel is based on the current location of the mobile device and the current location of the vehicle. The first arrow is combined with a view obtained by a camera of the mobile device or a view obtained by a camera of the vehicle.

Abstract: A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: receive at least one of expected upcoming traffic behavior or actual upcoming traffic behavior corresponding to an upcoming segment of a roadway being traversed by a vehicle; adjust a radiator hysteresis timer based on the expected upcoming traffic behavior or the actual upcoming traffic behavior; and transmit a control signal to an actuator to actuate a radiator fan based on the adjusted radiator hysteresis timer.

Abstract: A vehicle subscribed to an authentication system includes a wireless transceiver; and a controller, configured to responsive to receiving a wireless signal from a device identified as a key fob via the wireless transceiver, obtain history data reflecting time and location of the key fob associated with the vehicle detected via one or more entities subscribed to the authentication system, calculate a sanity value using the history data, such that a distant detection location from the vehicle location at a time before present time results in a lesser sanity value and a nearby detection location from the vehicle location at substantially the same time before the present time results in a greater sanity value, calculate a sanity threshold using at least one of the present time and the vehicle location, and responsive to the sanity value being greater than the sanity threshold, unlock a door of the vehicle.

Abstract: A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: receive at least one of expected upcoming traffic behavior or actual upcoming traffic behavior corresponding to an upcoming segment of a roadway being traversed by a vehicle; adjust a radiator hysteresis timer based on the expected upcoming traffic behavior or the actual upcoming traffic behavior; and transmit a control signal to an actuator to actuate a radiator fan based on the adjusted radiator hysteresis timer.

Abstract: Vehicle manufacturers may leverage one vehicle of a household to gain intelligence to determine whether a new vehicle may be purchased or an existing vehicle may be replaced for the household. Techniques include identifying a home geofence space that identifies the household at the household address for the vehicle. The sensor data from the vehicle can be used to identify other vehicles within the home geofence space. When other vehicles are identified that match appropriate criteria, the other vehicles may be associated with the household. Further observation of the other vehicles and the behavior of the members of the household can be used to identify when an existing vehicle of the household may be replaced and/or a new vehicle may be purchased. Upon determining that a new or replacement vehicle may be purchased, marketing materials may be provided to the household to aid the household with purchasing the new vehicle.

Abstract: The disclosure is generally directed to systems and methods for prioritizing driver warnings in a vehicle. In one example, a first sensor in the vehicle may detect a first driving event, such as, for example, another vehicle that is traveling in a blind spot of the driver. A second sensor in the vehicle may detect a second driving event, such as, for example, that the driver of the vehicle is tailgating another vehicle. A driver warning system in the vehicle produces a driver warning based on prioritizing one of the two driving events. For example, the driver warning system may prioritize a warning pertaining to the tailgating action over a warning pertaining to the vehicle moving in the blind spot. In some cases, the prioritization may be carried out by using historical information about the two driving events.