Abstract: A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to generate vehicle-level commands based on received vehicle operation commands. The received vehicle operation commands can comprise input commands corresponding to at least one of an autonomous vehicle (AV) mode of operation or a manual mode of operation. The processor is also programmed to generate target actuator commands based on the vehicle-level commands and transmit the target actuator commands to at least one actuator.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Methods and systems are provided for controlling an autonomous vehicle. In one embodiment, a method includes: A method of controlling an autonomous vehicle, comprising: receiving, by a processor, a first set of data obtained from an inertial measurement unit of the vehicle; receiving, by the processor, a second set of data obtained from a global positioning system of the vehicle; receiving, by the processor, a third set of data obtained from a camera of the vehicle; determining, by the processor, at least two vehicle states relative to markings of a lane by processing the first set of data, the second set of data, and the third set of data as measurement with an extended Kalman filter; and controlling, by the processor, the vehicle based on the at least two vehicle states.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.