Abstract: A method for estimation of a vehicle tire force includes: receiving, by a controller of a vehicle, a measured vehicle acceleration of the vehicle; receiving, by the controller, a measured wheel speed and a measured yaw rate of the vehicle; forming, by the controller, inertia matrices based on an inertia of rotating components of the vehicle; calculating torques at corners of the vehicle using the inertia matrices; estimating tire forces of the vehicle based on the measured vehicle acceleration, the measured wheel speed, and the inertia matrices; and controlling, by the controller, the vehicle, based on the plurality of estimated longitudinal and lateral tire forces.

Abstract: A method of controlling an active aerodynamic system of a vehicle includes calculating a first spring force estimated value from at least one sensed vehicle handling characteristic, and a second spring force estimated value from a nominal spring characteristic curve. When a difference between the first and second spring force estimated values is equal to or greater than a spring threshold value, a nominal spring characteristic curve is adjusted to define an adjusted spring characteristic curve, and the active aerodynamic system is controlled using the adjusted spring characteristic curve. When the difference between the first and second spring force estimated values is equal to or greater than the spring threshold value, a signal may also be engaged to provide a service recommendation.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes receiving, via a processor, image data of a surroundings of the vehicle. The method includes performing, via a processor, image analysis on the image data to identify road features. The method includes matching, via a processor, the identified road features to road features in a predetermined map to determine matched road features. The method includes determining, via a processor, global positioning data for the vehicle based on global positioning data in the predetermined map and the matched road features. The method also includes calibrating, via a processor, effective rolling radius of a wheel of the vehicle based at least on the global position data. The method further includes controlling, via a processor, a function of the vehicle based, in part, on the effective rolling radius.

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 processor-implemented method in a vehicle for performing automatic vehicle lateral control using a neural network for trajectory tracking is provided. The method includes receiving a desired vehicle trajectory; constructing, from the desired trajectory, desired waypoint data for a small number of desired waypoints at different look ahead distances in front of the center of gravity of the vehicle; and generating a steering angle command using a feedforward artificial neural network (ANN) as a function of vehicle speed and the desired waypoint data without modeling vehicle or tire dynamics. The vehicle steering actuator system provides steering control to cause vehicle steering to attempt to achieve the steering angle command.

Abstract: A system and method for determining a roadway bank angle based on vehicle information. The method may include the steps of: obtaining vehicle information from at least one vehicle, the vehicle information is obtained from at least one of a global navigational satellite system (GNSS) receiver and one or more onboard vehicle sensors, and the GNSS receiver and the one or more onboard vehicle sensors are installed in the at least one vehicle; performing a roadway bank angle determination process using the obtained vehicle information to obtain a roadway bank angle; and updating a representative roadway bank angle based on the roadway bank angle.

Abstract: 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.

Abstract: Systems, Methods and Apparatuses are provided for detecting surface conditions, which includes: an image scene captured by a camera wherein the image scene includes: a set of a plurality of regions of interest (ROIs); and a processor configured to receive the image scene to: extract at least a first and a second ROI from the set of the plurality of ROIs of the image scene; associate the first ROI with an above-horizon region and associate the second ROI with a surface region; analyze the first ROI and the second ROI in parallel for a condition related to an ambient lighting in the first ROI and for an effect related to the ambient lighting in the second ROI; and extract from the first ROI features of the condition of the ambient lighting and extract from the second ROI features of the effect of the ambient lighting on a surface region.

Abstract: Vehicles and steering systems for vehicles are provided. An exemplary steering system is provided for an automotive vehicle that includes road wheels and a rack mechanically coupled to the road wheels and laterally displaceable to change an orientation of the road wheels. The steering system includes a steering wheel mounted on a steering column and rotatable by a driver for inputting a steering command. The steering system also includes a lower column coupled to the rack. In the steering system, lateral displacement of the rack causes a rotational torque on the lower column. The steering system further includes a magneto-rheological coupling interconnected between the steering column and the lower column. The magneto-rheological coupling selectively communicates a desired portion of the rotational torque on the lower column to the steering column to provide haptic feedback to the steering column.

Abstract: 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.

Abstract: A control system for providing a yaw moment control action is provided. The control system comprises a command interpreter and a control segment. The command interpreter is configured to generate desired current vehicle states, when a vehicle is driven manually, wherein the current vehicle states comprise a target yaw rate state and a target lateral velocity state. The command interpreter is further configured to generate a desired states vector, when the vehicle is driven autonomously, using vehicle path planning instructions, wherein the desired states vector comprises current and future ideal yaw rate and lateral velocity states. The control segment is configured to generate a yaw moment control action using the desired current vehicle states when the vehicle is driven manually and generate a yaw moment control action using the desired states vector when the vehicle is driven autonomously.

Abstract: A method of controlling an active aerodynamic system of a vehicle includes calculating a first spring force estimated value from at least one sensed vehicle handling characteristic, and a second spring force estimated value from a nominal spring characteristic curve. When a difference between the first and second spring force estimated values is equal to or greater than a spring threshold value, a nominal spring characteristic curve is adjusted to define an adjusted spring characteristic curve, and the active aerodynamic system is controlled using the adjusted spring characteristic curve. When the difference between the first and second spring force estimated values is equal to or greater than the spring threshold value, a signal may also be engaged to provide a service recommendation.

Abstract: A vehicle subsystem includes an on-vehicle camera that is disposed to monitor a field of view (FOV) that includes a travel surface for the vehicle. A controller captures, via the on-vehicle camera, an image file associated with the FOV and segments the image file into a first set of regions associated with the travel surface and a second set of regions associated with an above-horizon portion. Image features on each of the first set of regions and the second set of regions are extracted and classified. A surface condition for the travel surface for the vehicle is identified based upon the classified extracted image features from each of the first set of regions and the second set of regions. Operation of the vehicle is controlled based upon the identified surface condition.

Abstract: A vehicle includes a plurality of on-vehicle cameras, and a controller executes a method to evaluate a travel surface by capturing images for fields of view of the respective cameras. Corresponding regions of interest for the images are identified, wherein each of the regions of interest is associated with the portion of the field of view of the respective camera that includes the travel surface. Portions of the images are extracted, wherein each extracted portion is associated with the region of interest in the portion of the field of view of the respective camera that includes the travel surface and wherein one extracted portion of the respective image includes the sky. The extracted portions of the images are compiled into a composite image datafile, and an image analysis of the composite image datafile is executed to determine a travel surface state. The travel surface state is communicated to another controller.

Abstract: A system and method for computationally estimating a tire normal force for use in vehicle antilock braking, adaptive cruise control, and traction and stability control by correcting measured accelerations with respect to the estimated road angles. The system and method are operative to measure an acceleration at three points on a sprung mass of the vehicle and estimate a tire normal force of a tire in response to the three acceleration measurements as an input to the vehicle controller.

Abstract: Examples of techniques for controlling a vehicle based on trailer position are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes extracting, by a processing device, a feature point on a trailer from an image captured by a camera associated with a vehicle, the trailer being coupled to the vehicle. The method further includes determining, by the processing device, a distance between the feature point on the trailer and a virtual boundary. The method further includes, responsive to determining that the distance between the feature point on the trailer and the virtual boundary is less than a threshold, controlling, by the processing device, the vehicle to cause the distance between the feature point on the trailer and the virtual boundary to increase.

Abstract: Examples of techniques for controlling a vehicle based on trailer sway are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes estimating, by a processing device, an estimated articulation angle between a vehicle and a trailer coupled to the vehicle. The method further includes calculating, by the processing device, an expected articulation angle between the vehicle and the trailer. The method further includes comparing, by the processing device, the estimated articulation angle and the expected articulation angle to determine whether the trailer is experiencing trailer sway. The method further includes, responsive to determining that the trailer is experiencing sway, controlling, by the processing device, the vehicle to reduce the trailer sway.

Abstract: A system and method for remotely guiding an autonomous vehicle. The method includes receiving, by a controller of the autonomous vehicle, captured information relating to a scene. Controlling the autonomous vehicle through the scene requires input from a remote operator. The method also includes prioritizing the captured information. The method also includes transmitting the captured information to the remote operator based on the prioritizing. Higher priority information is transmitted to the remote operator.

Abstract: A combined slip based driver command interpreter for a vehicle is provided which may be communicatively coupled to a steering wheel angle sensor, an acceleration pedal position sensor and a brake pedal position sensor, the combined slip based driver command interpreter including, but not limited to a memory configured to store a non-linear combined lateral slip model and a non-linear combined longitudinal slip model, and a processor, the processor configured to determine a driver's intended vehicle lateral velocity and a driver's intended vehicle yaw rate based upon the angle of the steering wheel, the position of the acceleration pedal, the position of the brake pedal, a longitudinal velocity of the vehicle, the non-linear combined lateral slip model and the non-linear combined longitudinal slip model.

Abstract: A vehicle, system and a method of driving a performance vehicle. The system includes a sensor for detecting a value of driver input to the vehicle, and a processor. The processor is configured to compare the value of the driver input to a threshold value for the driver input, switch to a performance mode operation for the vehicle when the value of the driver input is greater than the threshold value, generate a command at the vehicle based on the value of the driver input using a performance model of the vehicle activated in the performance mode, and activate a performance actuator of the vehicle to generate a dynamic parameter at the vehicle from the command.