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.

A universal machine learning based system for estimating a vehicle state of a vehicle includes one or more controllers executing instructions to receive a plurality of dynamic variables and corresponding historical data. The controllers execute a sensitivity analysis algorithm to determine a sensitivity level for each dynamic variable and corresponding historical data and select two or more pertinent dynamic variables based on the sensitivity level of each dynamic variable and the corresponding historical data. The controllers standardize the two or more pertinent dynamic variables into a plurality of generic dynamic variables, wherein the plurality of generic dynamic variables are in a standardized format that is applicable to any configuration of vehicle, and estimate the vehicle state based on the plurality of generic dynamic variables by one or more machine learning algorithms.

A steering control system for a vehicle that considers the limitations of at least one of the vehicle and the environment is contemplated. The steering control system can receive a vehicle characteristic, an environmental condition, a desired amount of turning, and a desired velocity of the vehicle. Based on some, or all of these parameters, the steering control system can determine at least one of a wheel torque, a wheel angle, a wheel camber, and a wheel suspension for a desired vehicle path to enhance vehicle performance.

A method is provided for predicting a risk for rollover of a working machine for load transportation. The method includes: obtaining ground topographic data of a geographical area located close to the working machine from a ground topographic detection system; extracting a ground gradient from the ground topographic data; obtaining weight information of the load being currently transported by means of an on-board load weighting system or by receiving load information originating from the device that loaded the load being currently transported; determining a current maximal allowed ground gradient for the working machine based on the weight information; and predicting a risk for working machine rollover if the working machine approaches a geographical area including a ground gradient exceeding or being close to the current maximal allowed ground gradient for the working machine.

A steering control system for a vehicle that considers the limitations of at least one of the vehicle and the environment is contemplated. The steering control system can receive a vehicle characteristic, an environmental condition, a desired amount of turning, and a desired velocity of the vehicle. Based on some, or all of these parameters, the steering control system can determine at least one of a wheel torque, a wheel angle, a wheel camber, and a wheel suspension for a desired vehicle path to enhance vehicle performance.

A method for detecting an unbalanced payload condition in a machine is disclosed. The method includes detecting, by a first sensor, a pressure exerted on each of one or more struts in the machine by a payload. The method further includes detecting, by a second sensor, one or more operational parameters associated with machine. Furthermore, method includes determining, by a controller, a center of gravity of the payload based on detected pressure, the one or more operational parameters, and one or more dimensions of the machine. Additionally, the method includes determining, by the controller, a force being exerted, by the payload, on each traction member of the machine based on the center of gravity of the payload. The method further includes detecting, by the controller, the unbalanced payload condition when the force, being exerted on at least one traction member of the plurality of traction members, exceeds a threshold value.

A vehicle operable to pull a trailer comprising a payload is provided, that includes a plurality of sensors configured to capture sensor data related to the vehicle, the trailer, or both, and a controller configured to (i) receive the sensor data from the plurality of sensors, (ii) determine, based on the sensor data, one or more parameters associated with the trailer, the payload, or both, (iii) update, based on an analysis of the one or more parameters, a confidence level associated with an operation of the vehicle with the trailer and the payload, and (iv) based on the confidence level, responsively execute an autonomous control strategy comprising one or more adjustments to the operation of the vehicle.

Disclosed is an apparatus and method for estimating a road profile for a vehicle. The apparatus includes a camera, processors, and a controller. The processors are configured to obtain a state of the vehicle including a behavior of the vehicle, and obtain a road height from information provided by the camera. The controller is configured to estimate the road profile by changing coordinates of the camera according to the behavior of the vehicle based on a vehicle height, compensating for the road height and a recognition road distance, and matching and filtering multiple road heights.

A saddle-straddling type motor vehicle on which an object is loadable for traveling with the motor vehicle. The motor vehicle includes a main body having a wheel, a motor that generates driving force for moving the main body, a wheel force calculator configured to calculate wheel force exerted between the wheel and a surface of a road on which the motor vehicle is traveling, and a wheel force corrector configured to correct the wheel force calculated by the wheel force calculator based on a condition of the object loaded on the motor vehicle.

A collision detection device on a motor vehicle for tracking a remote target vehicle for the detection of an imminent collision by fusing radar sensor data from a first environment sensor designed as a radar sensor with sensor data from a second environment sensor. First wheel acquisition data based on the radar sensor data from the first environment sensor and second wheel acquisition data based on sensor data from the second environment sensor are merged and a parameter of the target vehicle is established.