Gm Global Technolgoy Operations, Inc.

The University of Waterloo

Reza Zarringhalam

Mohammadali Shahriari

Amir Takhmar

Paul A Adam

Ashraf Abualfellat

Jimmy Lu

Brian M Porto

Tetyana V Mamchuk

Milad Jalaliyazdi

Kin Man Michael Wong

Bakhtiar Brian Litkouhi

Shih-Ken Chen

Amir Khajepour

Hassan Askari

Mohammed Raju Hossain

Mehdi Abroshan

Tushita Arun Sikder

Zhi Li

William Melek

Klaus Trangbaek

Seyedalireza Kasaiezadeh Mahabadi

Jackson Barry McGrory

Khizar Ahmad Qureshi

Jayant Sachdev

Puneet Bagga

Kurt L Fischer

Dorothy Lui

Amirreza Mirbeygi Moghaddam

Parisa Mahvelatishamsabadi

Jimmy Zhong Yan Lu

Ethan Thomas Dietrich

Nikolai K Moshchuk

Kevin Austin O'Dea

Wen-Chiao Lin

Seyedeh Asal Nahidi

Avshalom Suissa

Sayyed Rouhollah Jafari Tafti

Ehsan Asadi

Shiv G Patel

Gabriel T Choi

Constandi J Shami

Saurabh Kapoor

Daryl A Wilson

Namal P Kumara

Carlos E Arreaza

Apral S Hara

Rasoul Salehi

Shaun C Bowman

Christopher Michael Churay

Matthew Kempeinen

Alaeddin Bani Milhim

Haley M Dalzell

Ami Woo

Gurhari Singh

Mark Gazda

Benjamin L Williams

Joseph M Burdge

Lance G Lamson

Michelle Zirngibl Taylor

Joshua M Levin

Benjamin J Gaffney

Tara Craigen

Kibrom Yohannes

Vaibhav J Lawand

Jameson M Collins

Michael B Peppard

Janakan Chandrakumar

Michael J Reinker

Peitong Hu

Daniel James Cornelius

Zachary Lott

Ben Maccallum

Yongkyun Shin

Wenhao Wu

Klaus Tranbaek

Emily Frances Wolfangel

Patrick Francis Pirrmann

A system for collaborative steering in steer-by-wire (SBW) vehicles includes sensors, a rack motor altering a position of the vehicle's steerable road wheels and an emulator altering a torque and position of a vehicle hand wheel. A collaborative steering system application (CSSA) obtains, static and dynamic information about the vehicle and the vehicle's environment, and generates a rack torque and/or angle command to the rack motor and an emulator torque and/or angle command to the emulator. The CSSA adjusts between ADAS and manual steering ratios and automatically transitions control between ADAS SBW control and manual control. The CSSA smooths transitions between ADAS SBW control and manual steering control and adjusts hand wheel stiffness by altering the emulator torque command, and causes the rack motor and emulator to operate according to a kinematic model while adapting road wheel response and vehicle operator steering feel based on scenarios and features currently enabled.

Collaborative steering in steer-by-wire systems for automated driving

A system and method are provided for controlling a vehicle. In one embodiment, a system includes: a sensor system configured to generate sensor data sensed from an environment of the vehicle; and a control module configured to, by a processor, based on the sensor data, identify a gap in a lane line on a roadway in front of the vehicle, determine at least two points within the gap, determine a curve between the at least two points, compute a correlation measure based on the curve, generate lane stitching data based on data based on the curve and an evaluation of the correlation measure, and controlling one or more components of the vehicle based on the stitching data.

Lane stitching methods and systems for robust automated driving control

A method for controlling a steer-by-wire system, comprising receiving vehicle data and a steering request from a vehicle, determining whether a steering road wheel actuator of the vehicle has failed using the vehicle data, in response to determining that the steering road wheel actuator of the vehicle has failed, determining a target wheel slip of the vehicle based on the steering request, maintaining the target wheel slip of the vehicle while the vehicle is in motion; and adjusting a wheel speed of at least one wheel of the vehicle based on a feedback signal, wherein the feedback signal is indicative of a road wheel angle while the vehicle is in motion.

Architecture and method for steer-by-wire failure backup using direct yaw control actuators

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 method for probabilistic autonomous vehicle control includes receiving a plurality of unfiltered sensor signals from a sensor system of a vehicle and determining, in real time, a failure probability of the sensor system using the unfiltered sensor signals. The method further includes determining a failure probability of a plurality of estimation signals at each time step using the failure probability of the sensor system and determining a failure probability of a plurality of Advanced Driver Assistance System (ADAS) subfunction commands using the failure probability of the plurality of estimation signals at each time step. Further, the method includes determining remedial actions for the plurality of ADAS subfunction commands based on the failure probability of the plurality of ADAS subfunction commands.

Probabilisic system and method for autonomous vehicle control

Vehicles and related systems and methods are provided for mitigating lane departures, alternatively referred to as lane keeping assistance. One method of assisting vehicle operation involves determining a control trajectory for the vehicle over a prediction horizon that satisfies one or more steering angle constraints for operating a steering system of the vehicle based at least in part on a current steering angle, a first difference between the control trajectory and a reference lateral trajectory for the vehicle and a second difference between the control trajectory and a lane boundary, for example, by minimizing a weighted sum of the differences. The method continues by determining a steering angle command for the vehicle based at least in part on the control trajectory and autonomously operating one or more actuators onboard the vehicle in accordance with the steering angle command prior to the vehicle crossing the lane boundary.

Vehicle systems and autonomous lane departure mitigation methods

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

A method in a vehicle, includes: providing, via an HMI, a request to be followed indication responsive to receipt of a request to be followed from a following vehicle; providing, via the HMI, a request to enter a tether operating mode; entering the tether operating mode and selecting a tether goal between the lead vehicle and the following vehicle; providing, via the HMI, a tether mode indication that indicates that the lead vehicle is in the tether operating mode; monitoring a headway between the lead vehicle and following vehicle; adjusting a preplanned trajectory calculated by a driver assistance system to facilitate the following vehicle obtaining and maintaining the tether goal; modifying driver assistance system operation based on a level at which the headway is greater than the tether goal; and generating control signals for vehicle actuators to control the lead vehicle to facilitate the following vehicle maintaining the tether goal.

Virtual tethering for autonomous convoy

Vehicles and related systems and methods are provided for controlling a vehicle in an autonomous operating mode. One method involves a controller associated with a vehicle identifying a visual attention state associated with a driver of the vehicle based at least in part on output of an imaging device onboard the vehicle, determining, based at least in part on the visual attention state, a driver lane preference corresponding to an adjacent lane in a visual attention direction relative to a current lane of travel for the vehicle, adjusting a priority associated with the adjacent lane corresponding to the driver lane preference and autonomously operating one or more actuators onboard the vehicle to initiate maneuvering the vehicle from the current lane in a manner that is influenced by the adjusted priority associated with the adjacent lane.

Vehicle systems and methods for autonomous operation using driver attention

Methods and systems are provided that include one or more sensors configured to obtain sensor data pertaining to both a driver of a vehicle and an environment surrounding the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate determining, using the sensor data, when the driver is incapacitated; determining, using the sensor data, when a threat is detected for the vehicle; and taking action to avoid the threat when the driver is incapacitated and the threat is detected, via instructions provided by the processor.

Optimal engagement of automated features to assist incapacited drivers

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

Systems and methods are provided for managing transitions between operational modes of a vehicle. The system includes a controller configured to, by a processor: automatically transition between vehicular operational modes without initiation by the driver including a hands-off autonomous driving mode in which the processor controls lateral steering of the vehicle, a hands-on driving assistance mode in which the processor controls the lateral steering of the vehicle while the driver is holding the steering wheel, and a no control mode in which the driver controls the lateral steering of the vehicle. The transition between the operational modes is based on sensed data. The hands-off autonomous driving mode is prioritized over the hands-on driving assistance mode which is prioritized over the no control mode. The controller is further configured to display on a human-machine-interface a notification indicating that at least one of the operational modes is active or not available.

Systems and methods for transiting between automated driving operational modes

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 of controlling a vehicle. The methods and systems include switching to a second processor executed mode in response to determining that a range of perception information extends to a range end point that is closer to the vehicle than a first Look Ahead (LA) point. In the second processor executed mode: a motion planner requests a lateral controller to provide a closer LA point relative to the vehicle. The lateral controller determines the closer LA point and sends the closer LA point to the motion planner. The lateral controller generates control commands for an EPS system based on an error between a desired trajectory and an actual trajectory at the closer LA point. The motion planner generates the desired trajectory based on perception data and the closer LA point.

Methods and systems for vehicle control under degraded lane perception range

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

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Waterloo, Canada

Reza Zarringhalam