Steering Solutions IP Holding Corporation

Michael Story

Joachim J Klesing

Owen K Tosh

Patrik M Ryne

Pierre Claude Longuemare

Keyur R Patel

Peter D Schmitt

Ayyoub Rezaeian

Harold Li

Robert E Llaneras

Michelle Greb

Anthony J Champagne

Farhad Bolourchi

Scott T Sanford

Mariam Swetha George

Rangarajan Ramanujam

Rakesh Mitra

Zaki Ryne

Tao Yang

Larry J Wilson

Michael J Lask

Emilio Quaggiotto

Joshua D Kirk

William D Bodeis

Brendan Dziobak

Stephen Kosek

A method for controlling an actuator in a domain controller architecture in a vehicle includes receiving, at a domain controller, data related to operation of the actuator. The data includes information indicative of outputs of an actuator controller configured to control the actuator. The domain controller is configured to operate in accordance with a first safety integrity level among a plurality of safety integrity levels. The actuator controller is configured to operate in accordance with a second safety integrity level below the first safety integrity level. The method includes selectively supplying, from the domain controller based on the received data, a disable signal to a hardware component of the actuator controller to disable control of the actuator by the actuator controller. The disable signal is generated in accordance with the first safety integrity level and the hardware component is configured to operate in accordance with the first safety integrity level.

QM actuators with an ASIL-D domain controller

A method for controlling an actuator. The method includes generating, in response to receiving a torque command signal from a first controller, an actuator control signal. The method also includes selectively controlling the actuator based on the actuator control signal. The method also includes, in response to identifying a fault associated with the first controller: generating, responsive to a determination that a partition associated with a second controller includes a fallback indicator, a fallback actuator control signal; and selectively controlling the actuator based on the fallback actuator control signal.

Generic actuator with customized local feedback

A method for distributed processing includes receiving an idle time and at least one task execution characteristic corresponding to each respective processor of a plurality of processors, wherein at least one processor of the plurality of processors is remotely located from other processors of the plurality of processors. The method also includes identifying a target processor of the plurality of processors to execute a task based on the idle time and the at least one task execution characteristic of the target processor. The method also includes communicating, to the target processor, a task request requesting the target processor execute the task and, in response to receiving a communication from the target processor indicating acceptance of the task, communicating, to the target processor, instructions for executing the task.

Systems and methods for decentralized-distributed processing of vehicle data

A method for dynamic software management includes receiving, at a source processor, an idle time and at least one task execution characteristic of corresponding to respective processors of one or more other processors. The method also includes identifying a target processor of the one or more other processors capable of executing a task associated with the source processor based on the idle time and the at least one task execution characteristic of the target processor. The method also includes communicating, to the target processor, a task request requesting the target processor execute the task associated with the source processor. The method also includes, in response to receiving a communication from the target processor indicating acceptance of the task, communicating, to the target processor, instructions for executing the task.

System and method for decentralized vehicle software management

A method includes receiving a first input indicating at least a selected controller type and generating, based on the first input, a model that represents a controller corresponding to the selected controller type. The method also includes receiving a second input indicating at least one functional aspect of the selected controller type, updating, based on the second input, the model to represent the at least one functional aspect of the selected controller type, and compiling, using the model, a binary file that represents, at least, the at least one functional aspect of the selected controller type. The method also includes uploading the binary file to a controller corresponding to the selected controller type.

Middleware system and method

Technical features of a steering system include a control module that dynamically determines an operating mode based on a set of input signal values such as lateral acceleration signal values and corresponding handwheel position values. The control module dynamically determines and learns classification boundaries between multiple operating modes based the input signal values. The control module further calibrates the steering system according to operating mode that is determined using the classification boundaries.

Steering mode selection using machine learning

A method of transitioning from an autonomous driving mode to a manual driving mode for a vehicle is provided. The method includes comparing a steering device input angle to an autonomously controlled steering angle to determine a steering angle error. The method also includes comparing an acceleration or deceleration input to an autonomously controlled acceleration or deceleration input to determine an acceleration or deceleration error. The method further includes progressively transitioning to the manual driving mode in a weighted manner based on a confidence level factor determined by a calculation that factors in the steering angle error and the acceleration or deceleration error.

Transition governance system and method for autonomous vehicle

A host vehicle includes a driver re-engagement assessment system and an X-by-wire device adapted for both manual control and automated control by an automated guidance system. The driver re-engagement assessment system includes a controller, a user interface, and test execution module and a test evaluation module. The user interface is configured to interface with an occupant and output an occupant directive signal for manual control to the controller. The test execution module initiates an occupant re-engagement test upon receipt of the occupant directive signal by the controller. The test evaluation module is configured to receive an occupant performance signal indicative of occupant performance during the re-engagement test, and evaluate the occupant performance signal to determine a test pass result and a test fail result. The manual control of the host vehicle is assumed by the occupant upon the determination of the test pass result.

Driver re-engagement assessment system for an autonomous vehicle

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Bay City, MI, United States of America

Michael Story