Abstract: A vehicle computer comprises a processor and a memory. The memory stores instructions executable by the processor to detect debris flying above a roadway, to input vehicle sensor data to a first classifier that outputs a source of the debris, and based on the source of the debris, to compare sensor data representing the debris to stored reference data to determine a type of physical material included in the debris. The memory stores instruction to input the type of physical material and an environmental condition to a second classifier that outputs a risk assessment, and to actuate the vehicle based on the risk assessment.

Abstract: This disclosure is generally directed to harvesting electrical energy from RF signals that may be present in a vehicle. The RF signals may include cellular signals and Wi-Fi signals, for example. In an example system, an RF signal strength evaluator may be used to evaluate the RF signals in order to identify a strongest RF signal or a strongest band of RF signals that can be harvested to obtain electrical energy. An RF-to-electrical energy converter converts the RF signals(s) to electrical energy, which can be stored in an energy storage element. The energy storage element can be coupled to a device charger for charging various types of devices in the vehicle. In some instances, the system can be used to generate an ambient RF energy map that may be used by one or more vehicles to identify an optimal spot to park for harvesting RF signals.

Abstract: Guidance to a vehicle occupant is directed to manual adjustment of a height of a D-ring mechanism of a safety belt. First data of the occupant is collected which is indicative of a target height for the D-ring mechanism. Second data is collected indicative of a current height of the D-ring mechanism. The target height and the current height are compared to generate an adjustment amount whenever their difference is greater than a predetermined threshold. Visual guidance is presented to the occupant on an HMI display panel wherein the visual guidance describes taking an particular action to achieve the manual height adjustment of the D-ring mechanism. A further visual instruction is presented to the occupant on the HMI display panel wherein the visual instruction identifies the adjustment amount.

Abstract: A computer is programmed to determine a trajectory of a moving target based on data from one or more vehicle sensors. The computer is programmed to deploy an aerial drone from the vehicle to track the moving target based on the determined trajectory.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive sensor data of an occupant of a vehicle, identify a type of mask worn by the occupant based on the sensor data, select a sound filter according to the type of mask from a plurality of sound filters stored in the memory, receive sound data, apply the selected sound filter to the sound data, and perform an operation using the filtered sound data.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive sensor data of an occupant of a vehicle, identify a type of mask worn by the occupant based on the sensor data, select a sound filter according to the type of mask from a plurality of sound filters stored in the memory, receive sound data, apply the selected sound filter to the sound data, and perform an operation using the filtered sound data.

Abstract: The disclosure generally pertains to systems and methods for providing driver alerts inside a neighborhood. In an example embodiment, a neighborhood area network of computers is used to convey to a driver in the neighborhood, a driver alert about a driving impediment present on a road outside a residence. The driving impediment, which may be, for example, a vehicle, a trash receptacle, or an individual, is detected by a detection device (a camera, for example). The detection device informs a computer located in the residence of the driving impediment. The computer then communicates via the neighborhood area network with a computer in the vehicle to alert the driver. In some implementations, information pertaining to driving impediments in the neighborhood may be entered into a distributed ledger by using a blockchain mode of operation. The computer in the vehicle can access the distributed ledger to obtain this information.

Abstract: Proximity-based vehicle security systems and methods are provided herein. An example method includes determining a napping event of a vehicle occupant within a vehicle, determining, based on signals of external sensors of the vehicle, when an object has entered one of a plurality of distance-based zones during the napping event, each of the distance-based zones being associated with a unique security response, and invoking the unique security response of the one of a plurality of distance-based zones.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to identify an occupant in a passenger cabin of a vehicle, detect a position of a head of the occupant relative to the passenger cabin, apply a first filter to speech from the occupant based on the position of the head, generate a second filter, apply the second filter to the speech, adjust the second filter based on a difference between the speech of the occupant filtered by the second filter and a prestored profile of the occupant, and perform an operation using the speech filtered by the first filter and the second filter.

Abstract: Chionophobia intervention systems and methods are disclosed herein. An example method includes detecting snowfall from a vehicle sensor of a vehicle or a service provider, displaying a prompt on a human machine interface (HMI) to query a user regarding additional assistance in response to the detection of the snowfall, activating a first stage response after detecting the snowfall, determining when the first stage response is insufficient based on feedback received from the user, and activating a second stage response when the feedback received from the user indicates that the first stage response is insufficient.

Abstract: The disclosure generally pertains to systems and methods for detecting an occupancy of a back seat in a vehicle before a driver exits the vehicle. In one example method, a backseat occupancy alert system detects an activity that precedes the driver exiting the vehicle. For example, the system may detect that the driver has performed, or is performing, actions such as turning off the engine of the vehicle, placing the vehicle in a parked condition, and/or opening a door of the vehicle. The detection may be carried out, for example, by evaluating an image captured by one or more cameras in the vehicle. The system may then detect a failure by the driver to look towards a back seat of the vehicle, where, for example, a child may be seated in a car seat. The system may then produce an alert to prompt the driver to check the back seat.

Abstract: A computer-implemented method for detecting a working condition of one or more vehicle components includes communicating with a cellular communication module in a vehicle over a telecommunications network. A vehicle component characteristic or identifier for the vehicle components is received over the telecommunication network. One or more operation status identifiers for the one or more vehicle components based on data from the vehicle is also received. A location for servicing or purchasing the one or more vehicle components based on the vehicle component characteristic or identifier is determined. A service status of the one or more vehicle components based on the one or more operation status identifiers is also determined. Based on the service status, a message including an identification of the vehicle components and a service or purchase location for the vehicle components is generated. The message is transmitted to a terminal for display.

Abstract: Systems and methods are provided herein for platooning vehicles or other types of nodes. The platooning may involve receiving a request from a vehicle to initiate a platoon. In response to the request, another vehicle may indicate a desire to form the platoon with the requesting vehicle. Before the platoon is formed, a verification process may be performed to determine the eligibility of the vehicle to join a platoon, which may be based on a rating associated with the vehicle. Once the vehicle is verified, the platoon may be established. Upon establishment, the vehicles may proceed to coordinate actions, and a lead vehicle may be identified for the platoon. Vehicles may request to join and leave the platoon throughout the lifetime of the platoon. The platoon may eventually be dismissed, for example if the lead vehicle leaves the platoon and no one vehicle is willing and/or able to serve as lead vehicle.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to detect a potential hydroplaning area of a roadway based on topographic data and based on vehicle sensor data, and to actuate a component of a vehicle based on a location of the potential hydroplaning area.

Abstract: This disclosure is generally directed to harvesting electrical energy from RF signals that may be present in a vehicle. The RF signals may include cellular signals and Wi-Fi signals, for example. In an example system, an RF signal strength evaluator may be used to evaluate the RF signals in order to identify a strongest RF signal or a strongest band of RF signals that can be harvested to obtain electrical energy. An RF-to-electrical energy converter converts the RF signals(s) to electrical energy, which can be stored in an energy storage element. The energy storage element can be coupled to a device charger for charging various types of devices in the vehicle. In some instances, the system can be used to generate an ambient RF energy map that may be used by one or more vehicles to identify an optimal spot to park for harvesting RF signals.

Abstract: A computer is programmed to deploy an aerial drone to fly within a specified distance of a first vehicle. The computer is programmed to detect a second vehicle and then activate an aerial drone light.

Abstract: Vehicle backup warning notification systems and methods are disclosed herein. An example method can include determining a hazardous condition in an operating area around a vehicle based on user input of a first user at a first point in time, storing a warning message that indicates that the hazardous condition is present in the operating area, determining a second user driving the vehicle at a second point in time, determining that the stored warning message exists, and presenting the warning message for the second user driving the vehicle to notify the second user that the hazardous condition is present in the operating area.

Abstract: Systems and methods for securing limited drivability of a vehicle by impaired drivers using blockchain are provided. The vehicle system uses blockchain to protect and disclose such vehicle deactivation, prevent false enabling/disabling of a vehicle, and saves this information to a shared ledger. A sensor system located on the vehicle, e.g., alcohol interlock sensors, interior sensors, and exterior sensors, may have access to this information along with fleet managers, OEM, and/or users. For example, when the alcohol interlock sensor is activated, it transmits a test request. Subsequently, the other sensors may identify the request and look for a known person inside or in the proximity of the vehicle. In a similar manner, whether the test has been conducted, as well as the results of the test may be verified by the other nodes, e.g., sensors/modules in the vehicle. Upon confirmation that the driver is impaired, the vehicle may be deactivated.

Abstract: Exemplary embodiments described in this disclosure are generally directed to systems and methods for reducing anxiety in an occupant of a vehicle. In one exemplary method, a computer that is provided in a vehicle receives from a source such as a server computer, information that is used to determine a behavioral profile of an occupant of the vehicle. The computer utilizes the behavioral profile to identify a behavior characteristic of the occupant. The behavior characteristic is matched by the computer to one of various behavior categories such as an amaxophobia sufferer category or a controlling personality category. The computer then executes one or more operations in the vehicle based on the behavior category to which the occupant belongs. If the occupant belongs to the amaxophobia sufferer category, the computer may, for example, play an audio track, display a video clip, and/or change a driving characteristic of the vehicle.

Abstract: A vehicle includes: motor(s), local sensors, processor(s) configured to: receive an instruction including first properties of a target vehicle; verify the instruction; instruct the local sensors to scan at a first resolution; mark a scanned external vehicle, having second properties, as compatible or incompatible based on a comparison of the first and second properties; instruct the local sensors to scan at a second resolution upon marking the external vehicle as compatible.