Gm Global Technolgoy Operations, Inc.

Ashraf Abualfellat

Mohammadali Shahriari

Reza Zarringhalam

Brian M Porto

Mohammed Raju Hossain

Mehdi Abroshan

Tushita Arun Sikder

Lance G Lamson

Emily Frances Wolfangel

Paul A Adam

Klaus Trangbaek

Tetyana V Mamchuk

Hassan Askari

Milad Jalaliyazdi

Andrew Wassef

Jackson Barry McGrory

Zhi Li

Xuefei Yang

Henry Warren Grasman

Michelle Zirngibl Taylor

Vaibhav J Lawand

Michael B Peppard

Daniel James Cornelius

Dhaval Kavindra Sompura

Klaus Tranbaek

Sadaf Mohammadi

Christopher Ratliff

A vehicle control system includes a sensor for detecting a vehicle performance characteristic, and a processor for determining a severity of a vehicle system fault in response to the vehicle performance characteristic. The processor determines a safe disable location in response to the vehicle system fault. The processor generates a disable delay request indicative of the safe disable location and the vehicle performance characteristic. A vehicle controller controls a vehicle to proceed to the safe disable location in response to the disable delay request.

Smart vehicle disable

Methods and systems are provided for a vehicle towing a trailer. In one embodiment, a method includes: receiving, by a processor, sensor data from one or more sensors of the vehicle; estimating, by a processor, a steering torque value based on the sensor data; estimating, by the processor, a steering angle value based on the sensor data; determining, by the processor, a trailer tongue value based on the steering torque value and the steering angle value; and generating, by the processor, a control signal to control the vehicle based on the trailer tongue value.

Methods and systems for estimating trailer tongue values

An adaptive method for controlling the steering of an autonomous vehicle includes receiving a steering input. The steering input is indicative of a desired road wheel angle. The method also includes determining a commanded torque to achieve the desired road wheel angle. The method also includes measuring the road wheel angle of the vehicle (i.e., the measured road wheel angle). The method also includes executing a feedback control to determine a torque overlay. The feedback control includes determining, in real time, a current steering error vector of the vehicle. The feedback control includes determining the difference between the current steering error vector and a predetermined-steering error dynamics vector. The feedback control also includes determining a feedback gain correction vector. The feedback gain correction vector is a function of the difference between the current steering error vector and the predetermined-steering error dynamics vector.

Model-reference adaptive steering feedback control to reduce unforeseen oscillations in automated driving

A computer-implemented method that, when executed by data processing hardware of a vehicle, causes the data processing hardware to perform operations is provided. The operations include gathering sensor data, calculating one or more groove detection confidence values with the sensor data using one or more groove detection modules, evaluating the one or more groove detection confidence values using a road groove detection fusion module, determining whether a road groove is detected, communicating road groove data to an advanced driver-assistance system, and adapting trajectory and steering controls of the vehicle.

System and method for road groove detection and control in automated driving

Methods and systems are provided for a vehicle. In one embodiment, a method includes: initiating, by a processor, steering excitation according to a pattern while the vehicle is stationary; learning, by the processor, a load associated with a front axle of the vehicle based on the steering excitation; translating, by the processor, the load associated with the front axle of the vehicle to a load associated with a tongue of a trailer, and generating, by the processor, a trailer tongue load value based on the load associated with the tongue of the trailer.

Methods and systems for estimating trailer tongue load

A system and method for a vehicle control adaptation to a crosswind and a wind gust including a controller situated within a vehicle to receive wind data inputs. The wind data inputs are based on a location of the vehicle and include a sustained wind velocity, a sustained wind direction, and a wind gust level. The controller further receives vehicle measurement data from one or more sensors situated within the vehicle and determines a wind impact on the vehicle based on the wind data inputs and the vehicle measurement data. The controller further compensates for the wind impact by a feedforward control in response to a low bandwidth component of the wind data inputs and by a feedback control in response to a high bandwidth component of the wind data inputs. The controller generates a feedback and/or a control based on the wind impact.

Vehicle control adaptation to sustained wind levels and gusts

Methods and systems are provided for estimating vehicle parameters of a vehicle. A maximum desired vehicle acceleration and a minimum excitation acceleration in a first direction are determined. The minimum excitation acceleration is associated with generating an estimated vehicle parameter. A first control input for transmission to an advanced driver assistance system (ADAS) to apply a temporary excitation acceleration that is greater than the minimum excitation acceleration and less than the maximum desired vehicle acceleration is generated. The estimated vehicle parameter is generated using a vehicle parameter estimation observation model based on vehicle data received from at least one vehicle sensor. The vehicle data is generated in response to the application of the temporary excitation acceleration to the vehicle. The estimated vehicle parameter is transmitted to the ADAS of the vehicle for replacement of a previous vehicle parameter at the ADAS with the estimated vehicle parameter.

Systems and methods for estimating vehicle parameters

Methods and systems are provided for determining and mitigating vehicle pull force from passing other vehicles. In an exemplary embodiment, methods and systems are provided that include: obtaining sensor data via one or more sensors of a vehicle, the sensor data including both perception sensor data and vehicle dynamics sensor data; identifying, via a processor, one or more additional vehicles to be passed by the vehicle, using the perception sensor data; and predicting and determining, via the processor, a pull force for the vehicle that is caused by the passing of the vehicle by the one or more additional vehicles along with an impact of the pull force on the vehicle, based on both the perception sensor data and the vehicle dynamics sensor data, and control the vehicle to proactively mitigate the pull force on the vehicle; and vehicle with trailer when towing.

Identification and mitigation control of pull force impacts when passing large vehicles in automated driving

Automated driver assistance systems and methods for towing predict vehicle/trailer instabilities and adapt automated driving control to avoid them. A tow-vehicle includes a controller that, through an actuator system, controls speed and/or steering. A map system and/or a sensor system monitor a roadway on which the vehicle is travelling to identify a road profile located ahead of the vehicle over a prediction horizon. A projected trajectory for navigating the vehicle through the road profile over the prediction horizon and considering environmental conditions is determined. Before travel over the road profile, whether the projected trajectory through the road profile will result in exceeding a vehicle dynamic threshold is determined. When the projected trajectory will result in exceeding the vehicle dynamic threshold through the road profile, a control action is determined to prevent instability and optimize driver experience. The vehicle is operated through the road profile using the control action.

Tow-vehicle driving methods and systems for automated driving

Methods and systems are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a processor, that a lane centering feature is active in the vehicle; identifying, by the processor, a pattern of steering wheel torque; determining, by the processor, a driver requested offset based on a location of the vehicle and a location of a center of the lane; applying, by the processor, the driver requested offset to a planned trajectory of the vehicle; evaluating, by the processor, one or more duration conditions; and in response to the evaluating, selectively generating, by the processor, a control signal based on the planned trajectory with the driver requested offset.

Systems and methods for employing driver input for adapting path planning in lane centering applications

Methods and systems are provided for controlling a vehicle comprising an Electric Power Steering System (EPS). In an embodiment, a method includes learning, by a processor, a non-linearity of a boost factor associated with the EPS; determining, by the processor, a deboost factor based on an inverse relationship of the learned non-linearity of the boost factor associated with the EPS; and generating, by the processor, a steering command to the EPS based on the deboost factor.

Deboost methods and systems for active safety steering control

Systems and methods for controlling a vehicle are provided. The systems and methods provide a vehicle dynamics model that relates at least one input vehicle dynamics variable to at least one output vehicle dynamics variable. The systems and methods detect a crosswind impacting the vehicle by detecting a disturbance associated with the vehicle dynamics model caused by the crosswind and adapt control of the vehicle based on the detecting the crosswind impacting the vehicle.

Systems and methods for detection and mitigation of crosswind effects

In various embodiments, methods, systems, and vehicle apparatuses are provided. A method for lateral control of a steering system includes identifying at least one parameter of at least one lateral control feature that results in an optimized value in an outcome of control for a lateral control feature enabling robustness to an uncertainty; adaptively adjusting an output control signal generated by a vehicle trajectory controller coupled to the steering controller, by quantifying the uncertainty of an uncertain value in a lateral control feature; and sending a control command including at least a torque control or a wheel angle control to compensate for the uncertainty of the at least one uncertain value in the configuration of components of an electronic power steering (EPS) system associated with the vehicle variant by correcting at least one parameter of the at least one lateral control feature.

Methods, systems, and apparatuses for real-time adaptation of handwheel angle controls for robust automated driving to environmental conditions and model uncertainties

Growing community of inventors

Grand Blanc, MI, United States of America

Ashraf Abualfellat