Gm Global Technolgoy Operations, Inc.

Other

Gaurav Talwar

Xufang Zhao

Xu Fang Zhao

Rathinavelu Chengalvarayan

Md Foezur Rahman Chowdhury

Kenneth R Booker

Alaa M Khamis

Eli Tzirkel-Hancock

John L Holdren

Russell A Patenaude

Michael A Wuergler

Sherri J Voran-Nowak

Anthony J Sumcad

Eric T Hosey

Ron M Hecht

Uma Arun

Scott M Pennock

Luke J Popiel

Romeo D Garcia, Jr

Srinath Venkata Pendikatla

Omer Tsimhoni

Frank C Valeri

Scott M Reilly

Matthew Edward Gilbert-Eyres

Eray Yasan

Jeffrey Stefan

Kevin R Krause

Scott Thomas Droste

Timothy Grost

John J Correia

Neeraj Roy Gautama

Dipankar Pal

Robert D Sims, Iii

Dana Brian Fecher

Jeffery John Milton

Yun Qian Miao

Matthew C Neely

Cody R Hansen

William L Villaire

Kevin W Owens

Jesse T Gratke

Prabhjot Kaur

Dustin H Smith

Subhash B Gullapalli

Greg T Lindemann

Nicholas Constantine Sidiropoulos

Noah Sharkus

Gary J Rushton

Carmine F D'agostino

Mathew Anthony Clifford Keith Jones

Xufang Zhao, Iii

Maxim Burgman

Hossein Bonyan Khamseh

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.

Electric vehicle range management

A vehicle system includes a user device configured to produce acoustic sounds at varying frequencies. The vehicle system also includes a vehicle microphone for collecting acoustic data from the user device. Additionally, the vehicle system includes a vehicle processor for storing vehicle data including the acoustic data and a server communicatively coupled to the vehicle processor. In some examples, the server is configured to determine if the acoustic data match one or more predetermined frequencies of sound.

Vehicle system for detecting acoustic frequencies

Vehicles, systems and methods for acquiring a choreographic light pattern not previously available to the vehicles are presented. In some aspects, a target vehicle includes a processing system therein, an input interface coupled to the processing system and accessible to a user, and one or more image or other sensors positioned for capturing data from a source vehicle emitting a light pattern of interest. The processing system may scan and record a light pattern emitted by a portion of another vehicle in a line of sight of the vehicle. The scan uses data from the sensors and pattern recognition code. The identified light pattern is converted into metadata and transmitted to a central database. If the transmitted pattern is available and compatible with the target vehicle, the database may send a prompt to the target vehicle to download or purchase the pattern.

Pattern-based intelligent personalized choreography for software-defined vehicle

A communication augmentation system includes a camera, a transceiver and a computer. The camera is operation to record an image of users. The transceiver is operational to receive inbound messages from wireless devices. The inbound messages include an input content. The computer is operational to store registrations of the users, determine user locations where the users are located in response to facial profiles relative to the image, determine device locations where the wireless devices are located based on the inbound messages, associate the wireless devices with the users based on the user locations and the device locations, determine destinations of the inbound messages based on a comparison of input content to the identifiers, and transfer the input content and the destinations to the transceiver. The transceiver is further operational to transmit the input content in a plurality of outbound messages to the wireless devices based on the destinations.

Augmented in-vehicle communication

A language detection system includes data processing hardware and memory hardware in communication with the data processing hardware. The memory hardware stores instructions that when executed on the data processing hardware cause the data processing hardware to perform operations. The operations include issuing a vehicle prompt and determining responsiveness to the issued vehicle prompt, the responsiveness including an execution response and anon-responsive response. A language monitoring module is activated in response to the non-responsive response of the determined responsiveness and a spoken language is monitored within an interior cabin of a vehicle. A driver state is estimated based on the determined language, and a translation function is executed using a translation module in response to the estimated driver state.

Language detection system for a vehicle

A system for providing hearing accessibility for an occupant in a vehicle includes at least one display unit operatively connected to the vehicle. The at least one display unit has multiple sections, including a media screen adapted to display video content and a plurality of text boxes. A controller is in electronic communication with the at least one display unit, the controller being adapted to selectively execute a dictation engine. The controller has a processor and tangible, non-transitory memory on which instructions are recorded. The controller is adapted to receive audio input data from a plurality of sources. The controller is adapted to generate respective transcribed data from the audio input data, via the dictation engine. The respective transcribed data is displayed in the plurality of text boxes.

Dynamic audio signal transcription in a vehicle

The concepts include a user support system in the form of a microphone, a visual display arranged in a vehicle cabin, and a controller. The controller includes an instruction set that is executable to receive, via the microphone, a voice-based request from a user, and employ a virtual assistant to determine a user interaction in real time and to determine a specific intent for the voice-based request, including capturing metadata. A user interaction routine determines a user interaction parameter associated with the virtual assistant based upon the voice-based request from the user. A user sentiment analysis routine determines a user satisfaction parameter associated with the virtual assistant based upon the voice-based request from the user. The controller responds in real-time to the voice-based request based upon the user satisfaction parameter and the user interaction parameter that are associated with the virtual assistant.

System and method for a voice-activated user support system

A system for creating vehicle lighting atmosphere of a vehicle is provided. The system includes ambient lighting including a plurality of lights configured for illuminating an interior of the vehicle or an exterior of the vehicle with a selectable light color. The system further includes a computerized vehicle lighting controller, including programming to monitor an input useful to select an ambient lighting theme, select an ambient lighting theme based upon the input, and generate a command to control the ambient lighting based upon the ambient lighting theme.

System and method for creating a vehicle lighting atmosphere

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.

Vehicle load weight determination and distribution guidance

An automatic rain response system includes microphones of a vehicle, windshield wipers, and a controller. The microphones generate acoustic signals in response to rain. The controller is configured to receive a local weather condition, extract acoustic features from the acoustic signals, form feature vectors in response to the acoustic features and the local weather condition, classify the feature vectors to determine a current class among multiple classes, activate the windshield the wipers at a high speed in response to the current class being a heavy rain on a windshield class, activate the windshield wipers at a medium speed in response to the current class being a freezing rain on the windshield class, activate the windshield wipers at a low speed in response to the current class being a light rain on the windshield class, and deactivate the windshield wipers in response to the current class being a no rain class.

Automatic rain response system

A method for determining a sampling rate of occupancy data for a vehicle includes determining a vehicle speed and detecting whether an interrupt condition is present. If the speed is within a first speed range and no interrupt condition is detected, then a first sampling rate is selected for sampling the occupancy data. If the speed is within a second speed range that is higher than the first speed range, and/or if the interrupt condition is detected, then a second sampling rate which is faster than the first sampling rate is selected for sampling the occupancy data. A primary electronic control unit (ECU) may be configured for sampling the occupancy data. If the second sampling rate is selected and a computational demand of the primary ECU exceeds a predetermined threshold, then a portion of the computational demand may be transferred to one or more secondary ECUs for sampling the data.

System and method for determining a sampling rate of occupancy data for an automotive vehicle

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.

Automated deep learning based on customer driven noise diagnostic assist

A vehicle includes a plurality of microphones to obtain speech from a person outside the vehicle as an input signal and a sensor system to determine a location and orientation of the person relative to the vehicle. The vehicle also includes a controller to determine characteristics of the input signal and to determine whether to perform speech enhancement on the input signal based on one or more of the characteristics and the location and orientation of the person.

Context-aware signal conditioning for vehicle exterior voice assistant

A method for text feedback includes: receiving, by a controller, an utterance from a user; determining, by an automatic speech recognition engine of the controller, a plurality of speech recognition results based on the utterance from the user, wherein the speech recognition results include probable commands; determining, by the automatic speech recognition engine of the controller, a plurality of confidence scores for each of the plurality of speech recognition results; determining, by the controller, a text characteristic for each of the plurality of probable commands as a function of the confidence scores for each of the plurality of speech recognition results; and commanding, by the controller, a display to show text corresponding to each of the plurality of probable commands with the text characteristic determined by the controller.

Intelligent text and voice feedback for voice assistant

A method and associated system for recognizing speech using multiple speech recognition algorithms. The method includes receiving speech at a microphone installed in a vehicle, and determining results for the speech using a first algorithm, e.g., embedded locally at the vehicle. Speech results may also be received at the vehicle for the speech determined using a second algorithm, e.g., as determined by a remote facility. The results for both may include a determined speech topic and a determined speech slotted value, along with corresponding confidence levels for each. The method may further include using at least one of the determined first speech topic and the received second speech topic to determine the topic associated with the received speech, even when the first speech topic confidence level of the first speech topic, and the second speech topic confidence level of the second speech topic are both a low confidence level.

Speech recognition arbitration logic

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Novi, MI, United States of America

Gaurav Talwar