A machine-vision vehicle wheel alignment measurement system configured with at least one optical sensor to acquire images of optical targets disposed within an operative field of view. The system further includes a processing system configured with software instructions to determine relative spatial positions and orientations of one or more optical targets visible within images acquired by the optical sensor. The processing system is further configured with software instructions to automatically identify an axle count and axle configuration for a vehicle undergoing an alignment inspection or service using the determined relative spatial positions and orientations of the visible optical targets.

A method and apparatus that detect wheel misalignment are provided. The method includes predicting a self-aligning torque parameter based on a regression model determined from a dataset including one or more from among a steering wheel angle parameter, a speed parameter, a torsion bar torque parameter, a lateral acceleration parameter, and a power steering torque parameter, comparing a measured self-aligning torque parameter and the predicted self-aligning torque parameter, and outputting a wheel alignment condition indicating whether the wheel alignment is proper if the self-aligning torque parameter and the predicted self-aligning torque parameter are within a predetermined value based on the comparing.

An apparatus for automatically evaluating chassis or wheel alignment measurement data comprises: a memory device configured to store a number of chassis data records, with each chassis data record containing at least one chassis parameter and a tolerance range allocated to each chassis parameter; a provisioning device configured to provide a data record of current chassis parameters, which comprises at least one current chassis parameter; a selection device configured to select, on the basis of the data record provided by the provisioning device, a subset of chassis data records from the chassis data records stored in the memory device; and a determination device configured to determine the proportion of the chassis data records from the subset of chassis data records for which the current chassis parameter's of the data record provided by the provisioning device are within the specified tolerance ranges.

A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

A wheel alignment detection system for a vehicle includes a plurality of sensors and a controller. Each of the plurality of sensors is configured to generate a signal. The controller is in communication with the plurality of sensors and is configured to: detect an external force exerted on the vehicle based on the signal from at least one of the plurality of sensors; determine whether the external force exerted on the vehicle has a magnitude that is between a first predetermined value and a second predetermined value; and command the vehicle to provide an alert in response to determining that the magnitude of the external force exerted on the vehicle is between the first predetermined value and the second predetermined value, wherein the alert is indicative that a wheel alignment check should be performed.

A method of instance segmentation in an image and a system for instance segmentation of images. The method includes identifying, with a processor, a starting pixel associated with an object in an image, the image having a plurality of rows of pixels, the starting pixel located in a row of the plurality of rows; identifying, with the processor, at least one pixel located in an adjacent row to the row in which the starting pixel is located, the at least one pixel being part of the same object as the starting pixel; iterating the previous two identification steps using the at least one identified adjacent row pixel as a start pixel for the next iteration; and connecting, with the processor, the at least one identified adjacent row pixels to form polylines representing the object.

A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

A non-contact sensor for determining orientation of an object, such as a tire and wheel assembly of a vehicle, includes a projector assembly having a light emitter, a lens assembly and a mask, with the mask including mask apertures and the light emitter configured to project light through the lens assembly and mask apertures and onto the object, and with the mask apertures creating a light pattern of projected light onto the object. The sensor also includes an imager configured to image reflections of the light pattern from the object, and a processor. The projector assembly and imager are angled with respect to one another, and the processor is configured to process imaged reflections of the light pattern to derive the orientation of the object, such as the alignment orientation of the tire and wheel assembly.

A vehicle wheel alignment system includes a pair of wheel mounted targets, a pair of reference targets mounted to a stationary reference, a pair of gravity sensors, and a pair of vehicle-mounted active heads mounted on first and second sides of the vehicle. The active heads each have an image sensor for producing image data of one of the reference targets and one of the wheel mounted targets. The gravity sensors are disposed on each side of the vehicle in a known relationship to either the respective reference targets or the image sensors. A data processor calculates, using the image data, a plurality of poses of the wheel mounted targets as the vehicle wheels rotate; calculates a vehicle drive direction using the target poses and a measured orientation relative to gravity from the gravity sensors; and calculates a wheel alignment measurement using the vehicle drive direction.

A portable vehicle alignment system has a vertical central column with a carriage movable along its length, and a pair of camera arms pivotably attached to the carriage, each with a camera pod. The camera pods each have a camera for capturing image data of a respective vehicle-mounted target. One pod also has a calibration target disposed in a known relationship to its camera, and the other pod has a calibration camera disposed in a known relationship to its camera for capturing images of the calibration target. The camera arms pivot between an extended position where the cameras are disposed to capture image data of the vehicle targets and the calibration camera is disposed to capture images of the calibration target, and a folded position where the aligner has a width smaller than the width between the camera pods.