Gm Global Technolgoy Operations, Inc.

Shige Wang

Wei Tong

Shuqing Zeng

Xiaofeng Frank Song

Unmesh Dutta Bordoloi

Chang Liu

Stephen G Lusko

Roman L Millett

Upali Priyantha Mudalige

Donald K Grimm

Sourav Dey

Praveen Choudhury

Stephen N McKinnie

Ming Yang

Bakhtiar Brian Litkouhi

Xinyu Du

Jinsong Wang

Yiran Hu

Roy J Mathieu

Prakash Mohan Peranandam

Arun Adiththan

Soheil Samii

Ramesh Sethu

Steven E Muldoon

Wenyuan Qi

Massimo Osella

Joseph Gerard D'Ambrosio

Richard Gordon

James T Kurnik

James K Thomas

Trenton W Haines

Mark A Zerbini

Paolo Giusto

Farui Peng

Xian Zhang

Gurmitsingh M Banvait

Joseph G D Ambrosio

Jiang-Ling Du

Shane M Boehner

Sidharth Nakra

Osman Eser Atesoglu

Gopichand Movva

A dynamic side blind zone method includes determining that a host vehicle is approaching a first lane that is nonparallel to a second lane. The host vehicle is moving in the second lane. The method further includes activating an adaptive side blind zone alert system of the host vehicle in response to determining that the host vehicle is approaching the first lane that is nonparallel to the second lane, determining a warning zone in response to activating the adaptive side blind zone alert system of the host vehicle, and detecting a remote vehicle inside the warning zone after determining the warning zone. The remote vehicle is moving in the first lane. The method further includes providing an alert to a vehicle user of the host vehicle in response to detecting that the remote vehicle is inside the warning zone.

Adaptive side blind zone alert system and method

A perception processing system includes a memory and a main controller. The main controller includes modules and implements a data processing pipeline including algorithm stages, which are executed in parallel relative to sets of data and are executed sequentially relative to each of the sets of data. The algorithm stages share resources of the modules and the memory to process the sets of data and generate perception information. One of the modules executes global and local controllers. The global controller sets a processing rate for the local controllers. The local controllers monitor current processing rates of the algorithm stages. When one of the current processing rates is less than the set processing rate, the corresponding one of the local controllers sends a first signal to the global controller and in response the global controller sends a broadcast signal to the local controllers to adjust the current processing rates.

Perception processing with multi-level adaptive data processing flow rate control

A method for validating an autonomous vehicle performance using nearby traffic patterns includes receiving remote vehicle data. The remote vehicle data includes at least one remote-vehicle motion parameter about a movement of a plurality of remote vehicles during a predetermined time interval. The method further includes determining a traffic pattern of the plurality of remote vehicles using the at least one remote-vehicle motion parameter. The method includes determining a similarity between the traffic pattern of the plurality of remote vehicles and movements of the host vehicle. Further, the method includes determining whether the similarity between the traffic pattern of the plurality of remote vehicles and movements of the host vehicle is less than a predetermined threshold. Also, the method includes commanding the host vehicle to adjust the movements thereof to match the traffic pattern of the plurality of remote vehicles.

Method and system for validating autonomous vehicle performance using nearby traffic patterns

An on-demand, feature focused data collection system of an automobile vehicle includes at least one data collection device provided with an automobile vehicle. A data collection unit receives data from the at least one data collection device in response to a data collection request submitted by a user. A data scene group combines portions of the data received by the data collection unit and stored in the data collection unit of the automobile vehicle or at a remote server. A control logic device receives the data collection request and activates collection of the data. The control logic device includes: a data collection strategy which differs if different types of the data are available; a reference algorithm loaded or deployed; a storage capacity allocated for the data; and a storage policy employed to save the data.

System and apparatus for on-demand, feature focused data collection in autonomous vehicles and autonomous driving systems

A computing system including a cooperative system architecture for cataloging, informing, sharing, and managing engineering assets within an organization includes a user management subsystem for creating a registered user profile associated with a specific user of the computing system. The registered user profile includes user metadata that provides identifying characteristics of the specific user. The computing system includes an asset management subsystem including an asset repository for recording one or more engineering assets. The asset management subsystem modifies the user metadata of the registered user profile in response to the specific user recording an engineering asset in the asset repository. The computing system includes a test management subsystem including a test repository for recording one or more test bill of materials.

Cooperative system architecture for engineering asset management and sharing

Presented are embedded control systems with logic for computation and data sharing, methods for making/using such systems, and vehicles with distributed sensors and embedded processing hardware for provisioning automated driving functionality. A method for operating embedded controllers connected with distributed sensors includes receiving a first data stream from a first sensor via a first embedded controller, and storing the first data stream with a first timestamp and data lifespan via a shared data buffer in a memory device. A second data stream is received from a second sensor via a second embedded controller. A timing impact of the second data stream is calculated based on the corresponding timestamp and data lifespan. Upon determining that the timing impact does not violate a timing constraint, the first data stream is purged from memory and the second data stream is stored with a second timestamp and data lifespan in the memory device.

Intelligent vehicles with distributed sensor architectures and embedded processing with computation and data sharing

An automobile vehicle continuous validation system includes a backend collecting data from a vehicle fleet and wirelessly communicating with the vehicle fleet. The backend is in wireless communication with at least one client. A vehicle module is provided on-board individual ones of multiple automobile vehicles of the vehicle fleet and performing an on-board vehicle validation analysis. A fleet-based validation module provided either at the backend or cloud based manages data defining a configuration of and a capability of the multiple automobile vehicles of the vehicle fleet. A validation manager generates validation tasks based on a user's definition or a desired production of the validation tasks of the validation analysis and a fleet vehicle availability. A client-side module remote from the multiple automobile vehicles of the vehicle fleet has interface items applied by the at least one client seeking to perform the validation analysis.

System and method enabling validation-as-a-service for continuous validation of advanced driver assistance systems and autonomous vehicles

A system for an attention-based perception includes a camera device configured to provide an image of an operating environment of a vehicle. The system further includes a computerized device monitoring the image, analyzing sensor data to identify a feature in the image as corresponding to an object in the operating environment and assign a score for the feature based upon an identification, a location, or a behavior of the object. The computerized device is further operable to define candidate regions of interest upon the image, correlate the score for the feature to the candidate regions of interest to accrue a total region score, select some of the candidate regions for analysis based upon the total region scores, and analyze the portion of the candidate regions to generate a path of travel output. The system further includes a device controlling the vehicle based upon the output.

System and method for region of interest window generation for attention based perception

A method for facilitating uses of a code for vehicle experiences includes receiving code data from the code in a sign. The sign is disposed outside a host vehicle. The method further includes establishing a connection with a service using the code data obtained from the code and in response to establishing the connection with the service, receiving service data. The service data includes information about the service. The method further includes, in response to receiving the service data, controlling the host vehicle according to the service data received after establishing the connection with the service.

Method and system for facilitating uses of codes for vehicle experiences

A controller area network fault detection and recovery system and method may include a fault detection module, a fault remediation module, a checkpoint manager, and a recovery manager configured to select one or more of the fault remediation mechanisms based upon detected CAN faults. Remediation of detected CAN faults is controlled at a CAN driver software level in accordance with selected fault remediation mechanisms in a predetermined ordered hierarchy.

Controller area network fault detection and recovery

A vehicle communication and control system includes a servicing host capable of exchanging data with a vehicle. The servicing host provides a vehicle service and includes a service identifier (ID) that indicates the vehicle service. The vehicle is configured to actively detect the service ID and to determine the vehicle service in response to detecting the service ID. The vehicle and the servicing host establish a wireless connection to exchange data and automatically initiate the vehicle service in response to detecting the service ID.

Automated vehicle initiated servicing system

A signal processing system includes a central processing unit (CPU) in communication with an accelerator, and an instruction scheduler in communication with the accelerator. A first memory device including a first instruction set is configured to operate the accelerator, a second instruction set is configured to operate the CPU, and a second memory device is configured to receive a datafile. The accelerator includes a plurality of processing engines (PEs) and an instruction scheduler, the instruction set includes a plurality of operators, and the instruction scheduler is configured to implement the operators in the accelerator employing the PEs. The CPU employs the operators implemented in the accelerator to analyze the datafile to extract a feature therefrom.

Method and apparatus for a neural network

In one example implementation according to aspects of the present disclosure, a computer-implemented method includes capturing a plurality of images at a camera associated with a vehicle and storing image data associated with the plurality of images to a memory. The method further includes dispatching vehicle perception tasks to a plurality of processing elements of an accelerator in communication with the memory. The method further includes performing, by at least one of the plurality of processing elements, the vehicle perception tasks for the vehicle perception using a neural network, wherein performing the vehicle perception tasks comprises performing an activation bypass for values below a first threshold, and performing weight pruning of synapses and neurons of the neural network based at least in part on a second threshold. The method further includes controlling the vehicle based at least in part on a result of performing the vehicle perception tasks.

Activation zero-bypass and weight pruning in neural networks for vehicle perception systems

A method in a multiprocessor system for processing multiple perception streams is disclosed. The method comprises: reading data from a plurality of perception streams according to a reading schedule determined by a predetermined policy, each perception stream comprising perception data from a different perception sensor; assigning a unique identification tag to each perception stream; writing each perception stream with its unique identification tag to a server input queue based on the predetermined policy; and processing the tagged perception streams using a server. The processing includes: retrieving tagged perception streams from the server input queue; applying a processing algorithm to process the retrieved tagged perception streams; and outputting the processed perception streams to a server output queue. The method further includes retrieving the processed perception streams from the server output queue and dispatching each retrieved processed perception stream to an appropriate post-processing destination based on the tag associated with the retrieved processed perception stream.

Architecture and method supporting multiple vision stream using shared server on embedded platform

A method for controlling a vehicle includes: receiving, by a controller, route data, wherein the route data is continuously updated while the vehicle is moving, and the vehicle includes a plurality of vehicle operating modes; receiving, by the controller, feature data, wherein the feature data is information about a plurality of features needed for each of the plurality of vehicle operating modes; determining, by the controller, a plurality of ranges for each of the plurality of vehicle operating modes, wherein each of the plurality of ranges is a function of the route data and the feature data for each of the plurality of vehicle operating modes; and commanding, by the controller, a user interface to display a list of range-mode combinations, wherein the list of range-mode combinations includes the plurality of ranges for each of the plurality of vehicle operating modes.

Growing community of inventors

Northville, MI, United States of America

Shige Wang