Abstract: A method of calculating traction torque of a tire of a vehicle includes calculating a parameter vector using a first extended Kalman filter, calculating a state vector using a second extended Kalman filter, and calculating the longitudinal stiffness as a function of the parameter vector and the state vector. A method for computing traction torque of a vehicle includes computing the longitudinal stiffness of the tire using the first and second extended Kalman filters, and computing the traction torque as a function of the longitudinal stiffness of the tire and a linear speed difference between a tire speed of the tire and a vehicle longitudinal speed.

Abstract: A method for estimating a trailer wheel position includes identifying a first set of wheel locations in at least a first image. Each of the wheel locations in the first set of wheel locations is associated with a corresponding trailer angle. A subset of wheel locations is identified in the first set of wheel locations as being false positives and the false positives are removed from the first set of wheel locations. A quadratic regression is applied to the first set of wheel locations and a parabola curve is determined relating a y position in the at least the first image to an x position in the at least the first image. A trailer angle is determined. A current wheel location is estimated by applying the determined trailer angle to the parabola curve.

Abstract: A method for detecting a trailer presence includes identifying a region of interest within a video feed from one or more cameras secured to a vehicle. The video feed depicts a scene having a first pixel area, and the region of interest corresponds to a portion of the scene having a second pixel area that is less than the first pixel area. The method also includes determining an optical flow within the region of interest, and determining that a trailer is connected to the vehicle in response to the optical flow within the region of interest matching a predetermined pattern corresponding to a connected trailer. A camera monitoring system for a vehicle is also disclosed.

Abstract: A method of providing a trailer end line for a tractor-trailer includes determining a fixed point on a tractor, determining a trailer angle of a trailer, determining a trailer line that is arranged at the trailer angle from the fixed point, determining an intersection point between the trailer line and a trajectory of a reference point on the trailer, determining a trailer end point along the trailer line and offset from the intersection point, and displaying a trailer end awareness line based upon the determined trailer end point.

Abstract: A method for adjusting a human machine interface (HMI) element location in a commercial vehicle display includes displaying, on an electronic display of a commercial vehicle, images from a camera secured to the commercial vehicle that depict a trailer of the commercial vehicle and its surrounding environment; determining a reference location of a reference point of the trailer in the images; superimposing an HMI element in the images on the electronic display at an HMI location determined relative to the reference location; and detecting that the reference location has changed in the images, and adjusting the HMI location in response thereto. A camera monitoring system (CMS) for a vehicle and a method for a camera mirror system are also disclosed.

Abstract: A method of providing a trailer end line for a tractor-trailer includes determining a fixed point on a tractor, determining a trailer angle of a trailer, determining a trailer line that is arranged at the trailer angle from the fixed point, determining an intersection point between the trailer line and a trajectory of a reference point on the trailer, determining a trailer end point along the trailer line and offset from the intersection point, and displaying a trailer end awareness line based upon the determined trailer end point.

Abstract: A method for automatically panning a view for a commercial vehicle includes receiving a video feed from at least one camera defining a field of view. A plurality of objects in the video feed, includes at least one wheel and at least one line, are identified. A path of each object in the plurality of objects is tracked through an image plane of the video feed. A trailer angle corresponding to each path is identified, the identified trailer angle is associated with the corresponding path, thereby generating a plurality of trailer angle measurements. The plurality of paths are down selected to a single path and identifying a single trailer angle measurement corresponding to the single path.

Abstract: A method for estimating a trailer wheel position includes identifying a first set of wheel locations in a first image. Each of the wheel locations in the first set of wheel locations is associated with a corresponding trailer angle. The first set of wheel locations is clustered and a primary cluster in the first set of wheel locations is identified. A best fit curve is applied to the primary cluster. The best fit curve is a curve associating wheel position to trailer angle. An estimated wheel position is determined by applying a determined trailer angle to the best fit curve in response to the wheel being hidden in the first image. The estimated wheel position is output to at least one additional vehicle system.

Abstract: An error in a demand prediction of items is reduced. A data processing apparatus for processing data on a demand for multiple items includes a model learning unit that generates a prediction model for predicting the demand for the multiple items, and a demand prediction unit that predicts the demand for the multiple items by using the prediction model. The model learning unit inputs actual data of the demand for each item to a first neural network of each item, extracts a feature quantity of each item, and combines the feature quantity of each item to generate a second neural network that is a prediction model.

Abstract: A method of controlling a component of a powertrain of a vehicle is provided. The method comprises calculating an estimated clutch surface friction coefficient as a function of an initial clutch surface friction coefficient, a temperature of the clutch, and a rotational speed difference between a driving part and a driven part of the clutch; and adjusting a command signal to the component of the powertrain based upon the estimated clutch surface friction coefficient. A method of controlling a component of a powertrain of a vehicle comprises: estimating a clutch touchpoint xct of a clutch controlled by a clutch actuation system including a ballramp system, based on the variables of the system to determine the translation of the ball for which the clutch will transmit torque; and adjusting a command signal to the component of the powertrain based upon the estimated clutch touchpoint xct of the clutch.

Abstract: In view of the relevant background art, the present invention is to provide a system or apparatus which enables data in use for learning to be sorted out, thereby reducing the amount of data to be handled. Presenting one example of the control system according to the present invention, the control system including a first processing device to generate a learnt model; and a second processing device to operate employing the generated learnt model and provided with input means, wherein the second processing device transmits information input from the input means to the first processing device; and where the input information as transmitted is information belonging to an area different from an area designated with the learnt model, the first processing device generates an updated learnt model based on the information belonging to the different area as received and the learnt model.

Abstract: When multiple explanatory variables are automatically created, a huge amount of output suggestions causes a heavy burden on selecting the suggestion. A marketing support system is configured to include a suggestion extraction unit that accepts purchase data and analyzes a correlation between the purchase data to output a composite variable, a restriction filtering unit that accepts the composite variable and a restriction table to exclude the composite variable based on a restriction condition defined in the restriction table, and a result filtering unit that uses a measure result defined in the past to estimate an anticipated effect when a measure based on the composite variable is performed, and selects a plurality of explanatory variables.

Abstract: An error in a demand prediction of items is reduced. A data processing apparatus for processing data on a demand for multiple items includes a model learning unit that generates a prediction model for predicting the demand for the multiple items, and a demand prediction unit that predicts the demand for the multiple items by using the prediction model. The model learning unit inputs actual data of the demand for each item to a first neural network of each item, extracts a feature quantity of each item, and combines the feature quantity of each item to generate a second neural network that is a prediction model.

Abstract: In view of the relevant background art, the present invention is to provide a system or apparatus which enables data in use for learning to be sorted out, thereby reducing the amount of data to be handled. Presenting one example of the control system according to the present invention, the control system including a first processing device to generate a learnt model; and a second processing device to operate employing the generated learnt model and provided with input means, wherein the second processing device transmits information input from the input means to the first processing device; and where the input information as transmitted is information belonging to an area different from an area designated with the learnt model, the first processing device generates an updated learnt model based on the information belonging to the different area as received and the learnt model.

Abstract: When multiple explanatory variables are automatically created, a huge amount of output suggestions causes a heavy burden on selecting the suggestion. A marketing support system is configured to include a suggestion extraction unit that accepts purchase data and analyzes a correlation between the purchase data to output a composite variable, a restriction filtering unit that accepts the composite variable and a restriction table to exclude the composite variable based on a restriction condition defined in the restriction table, and a result filtering unit that uses a measure result defined in the past to estimate an anticipated effect when a measure based on the composite variable is performed, and selects a plurality of explanatory variables.

Abstract: For the purpose of reducing the processing amount in evaluating an effect of a measure with a KPI, a measure evaluation system is configured to have: a basic indicator calculation module grouping data into a subject and a non-subject and calculating basic indicators of the subject and the non-subject before measure execution; a basic indicator estimation module creating, for each basic indicator, an estimation model representing a relationship between the basic indicators of the subject and the non-subject and estimating an estimated basic indicator, which is exhibited when the measure is not executed on the subject, based on a basic indicator of the subject after measure execution and on the estimation model; and a KPI evaluation calculation module receiving a KPI definition formed of arithmetic calculation of basic indicators and calculating an estimated KPI value corresponding to the KPI definition with the KPI definition and the estimated basic indicator.