Abstract: A method for matching a vehicle with a user including receiving a user ride request for a vehicle from a plurality of available vehicles from a user, receiving a threshold vehicle risk score preference for the user, receiving a user risk score for the user, receiving a threshold user risk score preference for the plurality of available vehicles, identifying a subset of the plurality of available vehicles having a vehicle risk score at or below the threshold vehicle risk score preference of the user and a threshold user risk score preference at or above the user risk score of the user, and presenting the user with ride options for selecting one of the subset of the plurality of available vehicles of the subset of available vehicles for the user ride request.

Abstract: In accordance with one embodiment of the present disclosure, a method includes receiving, by a processor, a current location of a vehicle, a destination location, and a routing plan having a routing factor and a reward arrangement, planning, by the processor, a planned route from the current location to the destination location based on the routing factor of the routing plan, providing a direction to travel from the current location to the destination location via the planned route, determining a level of adherence based on a comparison of the planned route and an actual route on which the vehicle actually travels, and providing a reward based on the level of adherence and the reward arrangement.

Abstract: A vehicle system includes a vehicle body defining a vehicle interior and a vehicle exterior, one or more detection devices including at least one of a microphone and a camera structurally configured to receive data indicative of conditions within the vehicle interior or on the vehicle exterior, a sanitization device, and a controller communicatively coupled to the one or more detection devices and the sanitization device, the controller including a processor and a non-transitory computer readable and executable instruction set, which when executed, causes the processor to receives data from the one or more detection devices, determine a surface at least one of within the vehicle interior or on the vehicle exterior contacted by a user based at least in part on the data from the one or more detection devices, and direct the sanitization device to sanitize the surface.

Abstract: A vehicle system includes a detection device structurally configured to capture an image, a door lock, where the door lock is positionable between a locked position and an unlocked position, a controller communicatively coupled to the detection device and the door lock, the controller including a processor and a non-transitory computer readable and executable instruction set, which when executed, causes the processor to receive a captured image of a user from the detection device, determine whether the captured image of includes protective equipment worn by the user, and direct the door lock to move into the unlocked position in response to determining that the protective equipment in the captured image meets a configurable protective equipment baseline.

Abstract: A vehicle system includes a detection device structurally configured to capture an image, a door lock, where the door lock is positionable between a locked position and an unlocked position, a controller communicatively coupled to the detection device and the door lock, the controller including a processor and a non-transitory computer readable and executable instruction set, which when executed, causes the processor to receive a captured image of a user from the detection device, determine whether the captured image of includes protective equipment worn by the user, and direct the door lock to move into the unlocked position in response to determining that the protective equipment in the captured image meets a configurable protective equipment baseline.

Abstract: A method for matching a vehicle with a user including receiving a user ride request for a vehicle from a plurality of available vehicles from a user, receiving a threshold vehicle risk score preference for the user, receiving a user risk score for the user, receiving a threshold user risk score preference for the plurality of available vehicles, identifying a subset of the plurality of available vehicles having a vehicle risk score at or below the threshold vehicle risk score preference of the user and a threshold user risk score preference at or above the user risk score of the user, and presenting the user with ride options for selecting one of the subset of the plurality of available vehicles of the subset of available vehicles for the user ride request.

Abstract: A roving maintenance vehicle system includes a computing device having a processor and a non-transitory computer readable memory, a transceiver unit communicatively coupled to the computing device and a machine-readable instruction set stored in the non-transitory computer readable memory. The machine-readable instruction set causes the roving maintenance vehicle system to perform at least the following when executed by the processor: broadcast, via the transceiver unit, a notification of availability of the roving maintenance vehicle in an area, receive, via the transceiver unit, a status from one or more vehicles in response to the broadcast of the notification of the roving maintenance vehicle in the area, identify one or more vehicles that require service based on the status from the one or more vehicles, and dispatch the roving maintenance vehicle to a location of a first vehicle of the one or more vehicles that require service.

Abstract: A smart refueling service for vehicles which predicts when a vehicle will need refueling based on vehicle sensors and historical and/or predictive information. When analysis indicates the vehicle has insufficient fuel to reach a destination, and there are no refueling stations along the route, a drone is dispatched to refuel the vehicle. The service is a subscription service which registers and authenticates a vehicle and monitors the vehicle based on user preferences. The user preferences may be to refuel at a desired time of day, day of the week or at a desired location.

Abstract: An automated manufacturing defect detection system includes processing circuitry configured to receive historical parts statistics corresponding to a failure of parts used in a vehicle assembly, receive vehicle sensor statistics corresponding to a failure of parts of post manufactured vehicles, and receive historical assembly line statistics corresponding to a failure of assembly of parts during the vehicle assembly. Additionally, the processing circuitry is configured to generate a profile for one or more parts used in the vehicle assembly, receive an analysis of each of the one or more parts of the assembled vehicle, determine whether any of the one or more analyzed parts deviate from the profile generated for that part, and in response to a determination that any of the one or more analyzed parts deviate from the profile generated for that part by greater than an expected quality threshold, automatically communicate an alert corresponding to the deviation.

Abstract: An automated manufacturing defect detection system includes processing circuitry configured to receive historical parts statistics corresponding to a failure of parts used in a vehicle assembly, receive vehicle sensor statistics corresponding to a failure of parts of post manufactured vehicles, and receive historical assembly line statistics corresponding to a failure of assembly of parts during the vehicle assembly. Additionally, the processing circuitry is configured to generate a profile for one or more parts used in the vehicle assembly, receive an analysis of each of the one or more parts of the assembled vehicle, determine whether any of the one or more analyzed parts deviate from the profile generated for that part, and in response to a determination that any of the one or more analyzed parts deviate from the profile generated for that part by greater than an expected quality threshold, automatically communicate an alert corresponding to the deviation.

Abstract: A smart refueling service for vehicles which predicts when a vehicle will need refueling based on vehicle sensors and historical and/or predictive information. When analysis indicates the vehicle has insufficient fuel to reach a destination, and there are no refueling stations along the route, a drone is dispatched to refuel the vehicle. The service is a subscription service which registers and authenticates a vehicle and monitors the vehicle based on user preferences. The user preferences may be to refuel at a desired time of day, day of the week or at a desired location.

Abstract: A roving maintenance vehicle system includes a computing device having a processor and a non-transitory computer readable memory, a transceiver unit communicatively coupled to the computing device and a machine-readable instruction set stored in the non-transitory computer readable memory. The machine-readable instruction set causes the roving maintenance vehicle system to perform at least the following when executed by the processor: broadcast, via the transceiver unit, a notification of availability of the roving maintenance vehicle in an area, receive, via the transceiver unit, a status from one or more vehicles in response to the broadcast of the notification of the roving maintenance vehicle in the area, identify one or more vehicles that require service based on the status from the one or more vehicles, and dispatch the roving maintenance vehicle to a location of a first vehicle of the one or more vehicles that require service.

Abstract: Methods and systems of the present disclosure provide targeted advertisements to customers using facial recognition data and the number of customers present in a geo-fenced area. The system includes a customer detection module to detect the presence of customers in the geo-fenced area. Upon detection of the customers, an image collection system is activated to obtain images of the customers to generate facial recognition data. Using the facial recognition data, the system determines the number of customers in the geo-fenced location and then compares the number to a threshold number of customers. If the number of customers meets and/or exceed the threshold number, the facial recognition data is then used to determine various characteristics of the customers. The system then selects advertisements for the customers based on their characteristics. The advertisements are then transmitted to the customers.