Abstract:
An electric generation system for vehicular applications including a vehicle tire having a tread portion, a hub portion and a plurality of semi-rigid spokes extending radially from the hub portion to the tread portion, a plurality of piezoelectric devices affixed to at least one surface of each of the plurality of semi-rigid spokes such that a deformation of the tread portion of the vehicle tire results in a deformation of at least one of the plurality of spokes and at least one of the plurality of piezoelectric devices, and a charge accumulator for receiving an electric current generated in response to the deformation of the at least one of the plurality of spokes and for storing an electric charge accumulated in response to the electric current.
Abstract:
A system includes data processing hardware and memory hardware in communication with the data processing hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations including inputting cellular range data, barometric sensor data, GNSS data, and automotive inertial data into a Kalman filter and outputting from the Kalman filter an estimate of elevation distance of a vehicle based on the cellular range data, the barometric sensor data, the GNSS data, and the automotive inertial data.
Abstract:
A method for managing range of an electric vehicle includes acquiring temperature forecast data for an upcoming time period and determining a range of the electric vehicle over the upcoming time period in view of the temperature forecast data. The method also includes determining a driving distance from the electric vehicle to a stationary electric vehicle charging station. Additionally, the method includes informing a user of the electric vehicle if, at one or more times during the upcoming time period, the range of the electric vehicle will be less than a threshold relative to the driving distance from the electric vehicle to the stationary electric vehicle charging station. Further, another method for managing range of an electric vehicle may take into account distance to one or more intended destinations.
Abstract:
A method includes virtually dividing a cargo area of a vehicle into a plurality of virtual cells. The method also includes creating, by implementing machine learning, a load profile for the cargo area. The load profile indicates a weight estimate at each of the plurality of virtual cells based on a load in the cargo area. Guidance on moving the load within the cargo area is provided based on the load profile to balance the load in the cargo area.
Abstract:
Methods and apparatus are provided for diagnosing a vehicle. In one embodiment, a method includes: initiating, by a processor, a recording of a noise by at least one microphone based on user selection data from a user of the vehicle; receiving, by the processor, audio signal data based on the recording; generating, by the processor, vector data based on the audio signal data; processing, by the processor, the vector data with at least one trained machine, by the processor, learning model to determine a classification of the noise; predicting, by the processor, an action to be taken based on the classification; and storing, by the processor, the audio signal data, the classification, and the action in a datastore.
Abstract:
An infotainment system of a vehicle includes: a primary intent module configured to determine a primary intent included in voice input using automated speech recognition (ASR); and an execution module configured to, via a first hardware output device of the vehicle, execute the primary intent. A secondary intent module is configured to: based on the primary intent, determine a first domain of the primary intent; based on the first domain of the primary intent, determine a second domain; and based on the voice input and the second domain, determine a secondary intent included in the voice input using ASR. A display control module is configured to display a request for user input indicative of whether to execute the secondary intent. The execution module is further configured to, via a second hardware output device of the vehicle, execute the secondary intent in response to user input to execute the secondary intent.
Abstract:
A processor receives a broadcast in a vehicle, select audio data from the broadcast, processes the audio data selected from the broadcast, determines a phonetic pattern of the selected audio data based on the processing, selects additional instances of audio data from the broadcast that resemble the selected audio data, processes the additional instances of audio data from the broadcast, determine phonetic patterns of the additional instances of audio data, and selects a plurality of phonetic patterns from the phonetic pattern of the selected audio data and the phonetic patterns of the additional instances of audio data. A transmitter transmits the plurality of phonetic patterns to a server to determine an optimal pronunciation of the selected audio data based on a statistical analysis of the plurality of phonetic patterns and to add the optimal pronunciation of the selected audio data to a database used to recognize speech in the vehicle.
Abstract:
A system and method of performing speech arbitration at a client device that includes a neural network speech arbitration application, wherein the neural network speech arbitration application is configured to implement a neural network speech arbitration process, and wherein the method includes: receiving speech signals at a client device; generating and/or obtaining a set of inputs to be used in a speech arbitration neural network process, wherein the speech arbitration neural network process uses a neural network model that is tailored to speech arbitration and that can be used to determine whether and/or to what extent speech recognition processing of the received speech signals should be carried out at the client device; and receiving a speech arbitration output that indicates whether and/or to what extent the speech recognition processing of the received speech signals is to be carried out at the client device or at the remote server.
Abstract:
A system and method of identifying and generating preferred emojis includes: detecting at a wireless device a plurality of selected emoji; determining the frequency with which each emoji is selected; identifying a defined number of emojis from the plurality of selected emojis based on the frequency with which each emoji is selected; and creating a frequently-used emoji library for the identified emojis.
Abstract:
A system and method of controlling an automatic speech recognition (ASR) system includes: receiving speech at the ASR system from a vehicle occupant that includes a command to control a vehicle function; identifying a gate command from the speech; associating the identified gate command with the command to control the vehicle function; storing the associated gate command and vehicle command in a database; receiving additional speech at the ASR system from the vehicle occupant; detecting the gate command in the additional speech; and accessing the stored gate command and vehicle command from the database.