Disclosed herein are systems and methods for the in-situ determination of vehicle wheel position using an inertial measurement unit (IMU). In one aspect as the wheel is rotating, gyroscope measurements are used to find a slip angle defined between the direction of wheel travel and the direction of vehicle travel, to determine a toe alignment condition for the wheel. System and methods are also presented for using an accelerometer to measure slip angle and camber angle. Using an accelerometer or gyroscope, instantaneous wheel angle measurements can also be made to predict vehicle movement, and aid in autonomous steering and in-situ wheel alignment adjustments.

A method for the diagnostic assessment of the wheel alignment of a vehicle (2) equipped with wheels (3) having tyres (301) coupled to respective rims (302), comprises the following steps: in a longitudinal movement of the vehicle (2) in a forward travel direction with one wheel (3) on a longitudinal track (4A), until the wheel (3) surmounts a measuring platform (5A) located along the track (4A), acquiring a forward travel measurement signal, representing a lateral force applied to the platform and directed transversely to both the longitudinal direction and the weight force at a forward travel instant at which the wheel surmounts the measuring platform (5A) as it moves along the track (4A) in the forward travel direction; in a longitudinal movement of the vehicle (2) in a return travel direction opposite to the forward travel direction with the wheel (3) on the track (4A), until the wheel (3) surmounts the measuring platform (5A), acquiring a return travel measurement signal, representing a lateral force applied to the platform (5A) and directed transversely at a return travel instant at which the wheel (3) surmounts the measuring platform (5A) as it moves along the track (4A) in the return travel direction; processing the forward and return measurement signals in order to determine, for the wheel (3), at least an angle of camber and/or toe.

A vehicle wheel service system including a plurality of sensors positioned in proximity to a heavy-duty multi-axle vehicle, to measure angles associated with three or more axles of the vehicle without repositioning the mounting of the sensors after initiating a measurement procedure. Additional sensors, associated with a vehicle reference, such as the vehicle frame axis, are disposed to provide vehicle reference measurement data which is communicated to a processing system. The processing system is configured with software instructions to evaluate the measurement data and to determine various vehicle wheel alignment angle measurements and/or necessary vehicle adjustments for each axle relative to the vehicle reference or to a fixed axle having a determined relationship to the vehicle reference.

A system for checking the attitude angles of wheels is provided, in a manner that is known per se, with a vertical measuring or column 1 on which some transmitters and receivers of electromagnetic signals are installed—for example coherent light illuminators (typically lasers) and associated reflected light sensor—which overall define a group of distance sensors.

According to the disclosure, the proposed system is produced using distance sensors appropriately fitted on a single vertical measuring structure which is positioned, on a side of a movement path, where the vehicle equipped with wheels moves, that has a substantially transverse direction with respect to the acquisition direction of the distance sensors.

A heavy-duty vehicle measurement system utilizing displacement sensor modules disposed in housings on opposite sides of a vehicle inspection lane to acquire a set of displacement measurements associated with a moving heavy-duty vehicle. Displacement data along one or more measurement axes is acquired independently by each of the displacement sensor module to measure corresponding distances between the sensor module and points on a surface of the passing heavy-duty. A processing system is configured to receive and evaluate the set of displacement measurements, together with known parameters of the measurement system, to identify heavy-duty vehicle features, such as configuration, body panels, wheel assemblies, and tire surfaces, and to calculate heavy-duty vehicle parameters such as velocity, wheel rim or tire dimensions, axle relative orientations (scrub angles) and wheel assembly spatial orientations.

A vehicle wheel alignment system and method is provided for performing a rolling wheel axis of rotation and wheel spindle point calculation every time an alignment is performed. Embodiments include an aligner having a target fixedly attachable to a wheel of the vehicle; a camera for viewing the target and capturing image data of the target; and a data processor. The data processor receives the image data from the camera, and determines a vector pointing from the target origin to a wheel spindle point based on the captured target image data, when the vehicle is rolled while the wheel is on a substantially flat surface such that the wheel and target rotate a number of degrees. The data processor is further adapted to calculate an alignment parameter for the vehicle based at least in part on the wheel axis of rotation and the coordinates of the wheel spindle point.

A device for wheel alignment measurement comprises at least two sensors which are configured to record each time at least two images of the front wheels and the rear wheels of a vehicle passing by; and an evaluation device which is configured to evaluate the images recorded by the sensors in order to determine whether the vehicle has traveled along a straight line. The sensors are arranged such that a vehicle to be measured can pass between the at least two sensors. The evaluation device is configured to determine the geometric travel axis of the vehicle and/or the individual tracks of the wheels on the front axle and/or the rear axle of the vehicle when the evaluation of the images recorded by the sensors reveals that the vehicle has traveled along a straight line.

A time series waveform of detected vibration of a tire during travel is multiplied by a window function of a prescribed time width and a time series waveform for each time window is extracted to calculate a feature vector from the time series waveform for each time window. Thereafter, when determining the state of the road surface during travel using the feature vector for each time window and road surface models, a plurality of the aforementioned road surface models is constructed depending on the magnitude of a braking/driving force, the braking/driving force acting on the aforementioned tire is estimated, and the state of the road surface is determined using the road surface models, which depend on the aforementioned feature vector and the magnitude of the estimated braking/driving force. The aforementioned road surface models are constructed with learning data comprising time series waveform data of tire vibration obtained by causing a vehicle mounted with a tire provided with an acceleration sensor to travel on road surfaces in multiple road surface states.

A vehicle measurement station utilizing one or more displacement sensors disposed on each opposite side of an inspection region of a vehicle inspection lane to acquire displacement measurement data along associated measurement axes. At least a portion of the displacement measurement data is associated with the outermost wheel assemblies on an axle of a moving vehicle passing through the inspection region, and utilized to determine one or more vehicle characteristics, such as an axle total toe condition.

A vehicle wheel alignment system and method is provided for performing a rolling wheel axis of rotation and wheel spindle point calculation every time an alignment is performed. Embodiments include an aligner having a target fixedly attachable to a wheel of the vehicle; a camera for viewing the target and capturing image data of the target; and a data processor. The data processor receives the image data from the camera, and determines a vector pointing from the target origin to a wheel spindle point based on the captured target image data, when the vehicle is rolled while the wheel is on a substantially flat surface such that the wheel and target rotate a number of degrees. The data processor is further adapted to calculate an alignment parameter for the vehicle based at least in part on the wheel axis of rotation and the coordinates of the wheel spindle point.