Gm Global Technolgoy Operations, Inc.

The University of Waterloo

Nikolai K Moshchuk

Shih-Ken Chen

Bakhtiar Brian Litkouhi

Flavio Nardi

Jihan Ryu

Chad T Zagorski

Kausalya Singuru

Kevin Austin O'Dea

Aamrapali Chatterjee

Shuqing Zeng

Jin-Jae Chen

Valery Pylypchuk

David Andres Pérez Chaparro

Chandra S Namuduri

Youssef A Ghoneim

Jin-Woo Lee

SeyedAlireza Kasaiezadeh Mahabadi

Qingrong Zhao

David M Sidlosky

William Golpe

Rouhollah Jafari

David Andrés Pérez Chaparro

Hualin Tan

Weiwen Deng

Edward T Heil

Seyedalireza Kasaiezadeh Mahabadi

Richard J Knoll

Cheng-Foo Chen

Suresh Gopalakrishnan

Reza Zarringhalam

Curtis L Hay

Amir Khajepour

James Heath Holbrook

Patrick J Monsere

Yunjun Li

Sayyed Rouhollah Jafari Tafti

Steven W Holland

Qi Zhang

Sami Ahmed

Yubiao Zhang

Ehsan Hashemi

Raviraj U Nayak

John X Cui

Steven A Opiteck

Walter B Cwycyshyn

Yadollah Sabri

Xingping Chen

Jonathan Darab

Audrey Devin Porter

William Melek

Steven T Schweitzer

Yingmei Si

Simon E Zimmerman

Ivan Fadeev

Edward McLenon

O Kyung Kwon

Bridget M O'Brien-Mitchell

David Perez-Chaparro

Ping Mi

Jason D Ritter

Kelli Mandeville

A driverless testing system for a vehicle driven along a predefined route situated in a location remote from a ground station control station includes one or more ground station controllers located at the ground station control station that are in wireless communication with a plurality of actuators, one or more field sensors, and a plurality of vehicle instrumentation sensors by a network. The one or more ground station controllers execute instructions to instruct the plurality of actuators drive the vehicle along the predefined route based on a vehicle test pattern and monitor the plurality of vehicle instrumentation sensors for a plurality of operating parameters of the vehicle. In response to detecting one or more of the operating parameters of the vehicle are compromised, the one or more ground station controllers select an alternative state of operation of the vehicle.

Driverless testing system for a vehicle

Systems and methods for controlling an autonomous vehicle are described. A trajectory planner module provides a first trajectory to a trajectory control module. The trajectory control module determines parameters of the first trajectory. The trajectory control module compares the parameters to a respective threshold value. The trajectory control module obtains one or more alternative trajectories, determines parameters of each alternative trajectory, and compares the parameters of the alternative trajectory to a respective threshold value. The trajectory control module selects a trajectory for controlling the autonomous vehicle that has parameters which are within a range defined by the threshold values and controls the autonomous vehicle based on the selected trajectory. Thus, before handing back control to a driver, the trajectory control module selects from alternate trajectories for controlling the autonomous vehicle.

Selecting trajectories for controlling autonomous vehicles

A vehicle and a system and method of controlling the vehicle. The system includes a sensor and a processor. The sensor obtains a first estimate of a force on a tire of the vehicle based on dynamics of the vehicle. The processor is configured to obtain a second estimate of the force on the tire using a tire model, determine an estimate of a coefficient of friction between the tire and the road from the first estimate of the force and the second estimate of the force, and control the vehicle using the estimate of the coefficient of friction.

GPS enhanced friction estimation

Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: receiving a first surface value associated with a first road surface area in an upcoming environment of the vehicle; receiving a second surface value associated with a second road surface area in the upcoming environment of the vehicle; determining a change in surface value based on the first surface value and the second surface value; and in response to the change in surface value being greater than a threshold, adapting at least one of vehicle collision warning messages, vehicle braking control, vehicle steering control, and path planning based on the second surface value.

Vehicle lateral motion management with preview road surface information

A control allocation system for a vehicle includes an electric power steering (EPS) system, one or more redundant actuation systems for controlling a plurality of wheels of the vehicle, and one or more controllers in electronic communication with the EPS system and the one or more redundant actuation systems. The one or more controllers execute instructions to determine tracking errors and vehicle dynamics states based on a plurality of local path planning references and receive a fault signal indicating the EPS system is non-functional. In response to receiving the fault signal, the one or more controllers determine a plurality of corrective constraints in real-time. The one or more controllers solve a real-time constrained optimization problem for each sampling interval of the control allocation system to determine a plurality of control actions based on the plurality of corrective constraints and the tracking errors.

Control allocation system for path tracking in a vehicle

Autonomous control of a subject vehicle including a longitudinal motion control system includes determining states of parameters associated with a trajectory for the subject vehicle and parameters associated with a control reference determined for the subject vehicle. A range control routine is executed to determine a first parameter associated with a range control command based upon the states of the plurality of parameters, and a speed control routine is executed to determine a second parameter associated with a speed control command based upon the states of the plurality of parameters. An arbitration routine is executed to evaluate the range control command and the speed control command, and operation of the subject vehicle is controlled to achieve a desired longitudinal state, wherein the desired longitudinal state is associated with a minimum of the range control command and the speed control command.

Method and apparatus for longitudinal motion control of a vehicle

An automotive vehicle includes a vehicle-based charging unit including a receiving unit configured to receive power from a ground-based charging unit, the receiving unit including a multi-coil receiver, a first actuator operably coupled to the vehicle-based charging unit and configured to adjust a first position of the vehicle-based charging unit relative to the ground-based charging unit, and a controller configured to selectively actuate the first actuator. The controller is configured to receive first performance indicator data indicating a first alignment between the charging units, determine an alignment error between the charging units and calculate a first position adjustment of the vehicle-based charging unit, automatically control the first actuator to implement the first position adjustment of the vehicle-based charging unit, and receive second performance indicator data indicating a second alignment between the charging units, the second alignment resulting in a desired power transfer efficiency between the charging units.

Methods and systems for alignment of wireless charging modules

A vehicle including a Global Positioning System (GPS) sensor, an Inertial Measurement Unit (IMU), and an Advanced Driver Assistance System (ADAS) is described. Operating the vehicle includes determining, via the GPS sensor, first parameters associated with a velocity, a position, and a course, and determining, via the IMU, second parameters associated with acceleration and angular velocity. Roll and pitch parameters are determined based upon the first and second parameters. A first vehicle velocity vector is determined based upon the roll and pitch parameters, the first parameters, and the second parameters; and a second vehicle velocity vector is determined based upon the roll and pitch parameters, road surface friction coefficient, angular velocity, road wheel angles and the first vehicle velocity vector. A final vehicle velocity vector is determined based upon fusion of the first and second vehicle velocity vectors. The vehicle is controlled based upon the final vehicle velocity vector.

Method and apparatus for determining a velocity of a vehicle

A method for providing low speed lateral steering control for an autonomously driven or semi-autonomously driven vehicle includes obtaining a desired final vehicle position relative to a current vehicle position, and calculating, by one or more data processors, a target vehicle position based on the current vehicle position and the desired final vehicle position. The method further includes calculating, by the one or more data processors, a road wheel angle command value based on the target vehicle position; determining, by the one or more data processors, a control signal based on the calculated road wheel command value; and providing the control signal to a steering controller.

Lateral control for vehicle wireless charging guidance

A method and apparatus that determine parking feasibility are provided. The method includes determining a charging pad location based on information received from sensors or the charging pad, generating a path function corresponding to a path from a vehicle position to the charging pad location, determining whether a vehicle is within a parking maneuver feasibility region by comparing values of the generated path function, a minimum turning radius of the vehicle, and a maximum steering angle rate of the vehicle, and moving the vehicle to the charging pad location if the vehicle is in the parking maneuver feasibility region.

Apparatus and method that determine parking feasibility

Presented are automated driving systems for executing intelligent vehicle operations in mixed-mu road conditions, methods for making/using such systems, and vehicles with enhanced headway control for transitional surface friction conditions. A method for executing an automated driving operation includes a vehicle controller receiving sensor signals indicative of road surface conditions of adjoining road segments, and determining, based on these sensor signals, road friction values for the road segments. The controller determines whether the road friction value is increasing or decreasing, and if a difference between the road friction values is greater than a calibrated minimum differential. Responsive to the friction difference being greater than the calibrated minimum differential and the road friction value decreasing, the vehicle controller executes a first vehicle control action. Conversely, if the friction difference is greater than the calibrated minimum but the road friction value is increasing, the controller responsively executes a second vehicle control action.

Automated driving systems and control logic with enhanced longitudinal control for transitional surface friction conditions

A method and apparatus that control lateral movement of a vehicle are provided. The method includes receiving vehicle information and path information of the vehicle, determining a center of vehicle rotation from the vehicle information, minimizing a path tracking error based on the path information of the vehicle, determining a road wheel angle command or a steering torque command using non-linear optimization based on the minimized path tracking error, and controlling an actuator according to the road wheel angle command or steering torque command.

Method and apparatus for lateral movement control

A method and apparatus that control lateral movement of the vehicle during backward motion are provided. The method includes loading a desired backward path of vehicle, the backward path comprising waypoints to be traveled along during a rearward motion of the vehicle, reflecting the waypoints along a reflection axis perpendicular to a longitudinal axis that runs from front to back of the vehicle such that the reflected waypoints define virtual forward path; and controlling lateral movement of the vehicle to follow the waypoints along the forward path while the vehicle is traveling in a backward direction.

Method and apparatus that direct lateral control during backward motion

A method is provided for autonomously operating a vehicle. The method includes receiving, at a processor, at least vehicle state data and vehicle object environment data; generating, with the processor, an optimal path for the vehicle with a cost function based on the vehicle state data and the vehicle object environment data; identifying, with the processor, at least one critical condition constraint based on at least one of the vehicle or vehicle environment; modifying, with the processor, at least a first portion of the optimal path based on the at least one critical condition constraint to result in a short-range trajectory portion; generating a resulting trajectory with the short-range trajectory portion; and implementing the resulting trajectory on the vehicle.

Autonomous vehicle driving systems and methods for critical conditions

A method and system for controlling a vehicle to improve vehicle dynamics are provided. The method includes receiving data from a plurality of sensors which monitor vehicle dynamics by monitoring at least wheel and steering movements associated with a vehicle system used in controlling vehicle dynamics by control outputs from a holistic vehicle control system. Then, estimating states of the vehicle from computations of longitudinal and latitudinal velocities, tire slip ratios, clutch torque, axle torque, brake torque, and slip angles derived from the data sensed by the sensors from the wheel and steering movements. Finally, formulating a model of vehicle dynamics by using estimations of vehicle states with a target function to provide analytical data to enable the model of vehicle dynamics to be optimized and for using the data associated with the model which has been optimized to change control outputs to improve in real-time the vehicle dynamics.

Systems and methods for holistic vehicle control with collaborative steering, electronic limited slip differential (ELSD), powertrain and braking

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Grosse Pointe, MI, United States of America

Nikolai K Moshchuk