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: Methods and system are provided for controlling a vehicle. The methods and systems read sensors and estimate pneumatic trail for a tire of the vehicle based on the sensor readings. The methods and systems determine presence or absence of a tire lateral saturation condition based on a comparison of the estimated pneumatic trail for the tire of the vehicle with a pneumatic trail threshold indicative of a tire lateral saturation condition. When the tire lateral saturation condition is present, the methods and systems determine a control value and use the control value as an input to a vehicle control module. The vehicle control module is responsive to the tire lateral saturation condition based on the control value.

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: Methods and systems are provided for an improved system and method for validating vehicle lateral velocity estimation. The provided system and method employ an efficient validation algorithm to detect lateral velocity estimation faults. The method and system are robust to road uncertainties and do not require redundant estimations or measurements. The provided system and method offer a technological solution for real time validation of lateral velocity estimation using already existing vehicle sensors, and are independent of (i) road condition information, (ii) wheel torque information, (iii) tire model information, and (iv) tire wear information.

Abstract: A method for determining a thickness of water on a path of travel. A plurality of images of a surface of the path of travel is captured by an image capture device over a predetermined sampling period. A plurality of wet surface detection techniques are applied to each of the images. A detection rate is determined in real-time for each wet surface detection technique. A detection rate trigger condition is determined as a function of a velocity of the vehicle for each detection rate. The real-time determined detection rate trigger conditions are compared to predetermined detection rate trigger conditions in a classification module to identify matching results pattern. A water film thickness associated with the matching results pattern is identified in the classification module. A water film thickness signal is provided to a control device. The control device applies the water film thickness signal to mitigate the wet surface condition.

Abstract: Methods and systems are provided for analyzing tires of a vehicle utilizing camera images from one or more cameras mounted on the vehicle (or infrastructure). In one example, the method includes obtaining camera images of one or more tires of a vehicle, utilizing one or more cameras that are mounted on the vehicle, during operation of the vehicle; and processing the camera images, via a processor, in order to generate an analysis of one or more of the tires based on the images that were obtained via the one or more cameras that are mounted on the vehicle.

Abstract: Methods and systems are provided for analyzing tires of a vehicle utilizing camera images from one or more cameras mounted on the vehicle (or infrastructure). In one example, the method includes obtaining camera images of one or more tires of a vehicle, utilizing one or more cameras that are mounted on the vehicle, during operation of the vehicle; and processing the camera images, via a processor, in order to generate an analysis of one or more of the tires based on the images that were obtained via the one or more cameras that are mounted on the vehicle.

Abstract: Systems and method are provided for controlling a first vehicle. In one embodiment, a method includes: determining, by a processor, that a second vehicle is going to merge into a current lane of the first vehicle at a merge point; and in response to the determining: obtaining, by the processor, a velocity history of the second vehicle, determining, by the processor, a first time value associated with the first vehicle and the merge point; determining, by the processor, a second time value associated with the second vehicle and the merge point; determining, by the processor, an intention of the second vehicle based on the velocity history, the first time value, and the second time value; and selectively generating, by the processor a command to at least one of control the first vehicle and provide notification based on the intention.

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: A system and method for computationally estimating a directional velocity of a vehicle in real time under different configurations and road conditions 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. A time window is used to provide reliable mapped acceleration for the transient regions and maneuvers on gravel surfaces with high fluctuations in the acceleration measurement. Longitudinal and lateral accelerations are mapped from the vehicle's CG into the tire coordinates using the vehicle's geometry, lateral velocity, yaw rate, and the steering wheel angle to generate system matrices of the combined kinematic-force estimation structure.

Abstract: Methods and systems are provided for determining a road surface condition. In one embodiment, a method includes: receiving vehicle data; constructing, by the processor, a driver behavioral model based on the vehicle data; determining, by the processor, a surface condition based on the driver behavioral model; and generating a signal based on the surface condition.

Abstract: Methods and systems are provided for controlling a component of a vehicle. In one embodiment, a method includes: receiving, by a processor, data associated with a center of gravity of the vehicle; determining, by a processor, a wheel moment adjustment command for each wheel of the vehicle based on the received data; determining, by a processor, at least one control output based on driver commands and the wheel moment adjustment command for each wheel; and selectively controlling, by a processor, at least one component associated with at least one of an active safety system and a chassis system of the vehicle based on the at least one control output.

Abstract: A method for determining a snow covered surface condition of a path of travel. A beam of light is emitted at a surface of the path of travel by a light emitting source. An image of a path of travel surface is captured by an image capture device. The image capture device is mounted on the vehicle and captures an image in a downward direction. The captured image captures the beam of light emitted on the path of travel surface. Analyzing a subsurface scattering of the light generated on the path of travel surface by a processor. A determination is made whether snow is present on the path of travel. A snow covered path of travel surface signal is generated in response to the identification of snow on the path of travel.

Abstract: A method of reconstructing a detected faulty signal. A pitch sensor fault is detected by a processor. A signal of the detected faulty pitch sensor is reconstructed using indirect sensor data. The reconstructed signal is output to a controller to maintain stability.

Abstract: Methods and systems are provided for determining vehicle spin-out conditions including conditions indicative of a vehicle spin-out ahead of the vehicle actually spinning-out. The methods and systems receive motion parameters of a vehicle based on sensed signals from at least one vehicle sensor of an electronic power steering system and an inertial measurement unit. The method and systems estimate pneumatic trail based on a rate of change of self-aligning torque with respect to axle lateral force. The methods and systems determine vehicle spin-out conditions based on the estimated pneumatic trail. The methods and systems control at least one feature of a vehicle in response to the determined vehicle spin-out conditions.

Abstract: A system and method for correcting the calibration of a plurality of cameras on a mobile platform such as in a surround-view camera system on a vehicle based on changes in vehicle dynamics. The method includes reading measurement values from one or more sensors on the vehicle that identify a change in vehicle dynamics and defining the plurality of cameras and a vehicle body as a single reference coordinate system. The method also includes identifying the measured values as a rotation matrix and a translation vector in the coordinate system, and integrating the rotation matrix and the translation vector into a relationship between a vehicle coordinate system and a camera coordinate system to provide the calibration correction of the cameras.

Abstract: A method for determining a wet surface condition of a road. Capturing an image of a wheel of a remote vehicle traveling in an adjacent lane by an image capture device of a host vehicle. Identifying in the captured image, by processor of a host vehicle, a region of interest relative to the wheel where the region of interest is representative of where precipitation dispersion occurs. A determination is made whether precipitation is present in the region of interest. A wet road surface signal is generated in response to the identification of precipitation in the adjacent lane.

Abstract: A method for determining a wet surface condition of a road. An image of a road surface is captured by an image capture device of the host vehicle. The image capture device is mounted on a side of the host vehicle and captures an image in a downward direction. Identifying in the captured image, by a processor, a region of interest. The region of interest is in a region sideways to a face of the wheel. The region of interest is representative of where sideways splash as generated by the wheel occurs. A determination is made whether water is present in the region of interest. A wet road surface signal is generated in response to the identification of water in the region of interest.

Abstract: A method for localizing a vehicle in a digital map. GPS raw measurement data is retrieved from satellites. A digital map of a region traveled by the vehicle based on the raw measurement data is retrieved from a database. The digital map includes a geographic mapping of a traveled road and registered roadside objects. The registered roadside objects are positionally identified in the digital map by earth-fixed coordinates. Roadside objects are sensed in the region traveled by the vehicle using distance data and bearing angle data. The sensed roadside objects are matched on the digital map. A vehicle position is determined on the traveled road by fusing raw measurement data and sensor measurements of the identified roadside objects. The position of the vehicle is represented as a function of linearizing raw measurement data and the sensor measurement data as derived by a Jacobian matrix and normalized measurements, respectively.

Abstract: A method of determining a surface condition of a path of travel. A plurality of images is captured of a surface of the path of travel by an image capture device. The image capture device captures images at varying scales. A feature extraction technique is applied by a feature extraction module to each of the scaled images. A fusion technique is applied, by the processor, to the extracted features for identifying the surface condition of the path of travel. A road surface condition signal provide to a control device. The control device applies the road surface condition signal to mitigate the wet road surface condition.