Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

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 tire radius monitoring system for dynamically determining a tire effective radius for each of the wheels on a vehicle is described. The system includes a GPS sensor, a plurality of wheel speed sensors, and a controller. The controller determines, via the GPS sensor, a velocity vector related to longitudinal velocity of the vehicle. The controller determines wheel speeds for the plurality of vehicle wheels, and detects a no-wheel-slip state for the vehicle wheels and the velocity vector from the GPS sensor. The controller determines tire effective radii for the plurality of vehicle wheels based upon the velocity vector for the vehicle and the wheel speeds for the plurality of vehicle wheels during the no-wheel-slip state, and controls vehicle operation based upon the tire effective radii.

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 system to detect and avoid spilled cargo in an automobile vehicle, includes an automobile vehicle rear cargo area including a floor to temporarily receive a storage item in the cargo area. A lift gate is moved between a closed and latched position and a fully open position inclusive to allow loading and removal of the storage item. A vision system identifies the storage item when initially loaded in the cargo area and identifies if the storage item is initially positioned in a cargo spill position or subsequently moves to the cargo spill position. A cargo stop device is releasably connected to the lift gate. An operating system releasably stores the cargo stop device when the storage item is not in the cargo spill position and deploys the cargo stop device when the storage item is in the cargo spill position.

Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

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: A system and method for personalization of adjustable features of a vehicle. The system includes a processor and an actuator. The processor detectors key points of a person from a two-dimensional image and predicts a pose of the person. The processor translates a respective position of the key points from a two-dimensional coordinate system to a three-dimensional coordinate system based in part on the pose and measurements of distances between the key points. The processor determines a baseline configuration of an adjustable feature of the vehicle based in part on measurements between the key points in the three-dimensional coordinate system. The processor causes an actuator to adjust the adjustable feature to conform to the baseline configuration.

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 method includes obtaining information about a lead vehicle. The lead vehicle is traveling directly ahead of the host vehicle and the information includes velocity of the lead vehicle and a gap g between the host vehicle and the lead vehicle. Based on detecting a change in the velocity of the lead vehicle in the information, a corresponding desired acceleration is computed for the host vehicle using perceived acceleration of the lead vehicle to maintain the gap g within a specified range of gap values. The perceived acceleration of the lead vehicle is based on the change in the velocity indicated by the information. Based on a check of parameters involved in the computing the corresponding desired acceleration, a modified desired acceleration is computed for the host vehicle using a lag for the lead vehicle that results in an intended acceleration of the lead vehicle differing from the perceived acceleration.

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 tire radius monitoring system for dynamically determining a tire effective radius for each of the wheels on a vehicle is described. The system includes a GPS sensor, a plurality of wheel speed sensors, and a controller. The controller determines, via the GPS sensor, a velocity vector related to longitudinal velocity of the vehicle. The controller determines wheel speeds for the plurality of vehicle wheels, and detects a no-wheel-slip state for the vehicle wheels and the velocity vector from the GPS sensor. The controller determines tire effective radii for the plurality of vehicle wheels based upon the velocity vector for the vehicle and the wheel speeds for the plurality of vehicle wheels during the no-wheel-slip state, and controls vehicle operation based upon the tire effective radii.

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: A method and associated system for selecting a charging station for a subject vehicle is described, and includes determining a state of charge of an on-vehicle DC power source arranged to supply electric power to a propulsion system for the subject vehicle. A travel route to a destination point is determined, and locations of a plurality of charging stations proximal to the travel route are identified. Desired states and corresponding weighting factors for a plurality of user-selectable parameters are determined, and a sorting routine is executed to rank the plurality of charging stations proximal to the travel route based upon the desired states and corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the on-vehicle DC power source. One of the charging stations is selected based upon the ranking, and a charging reservation is scheduled.

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.