Abstract: A method for determining a tire tread wear estimation of a tire includes receiving, by a controller, a direct tire tread wear measurement, when available, performing an indirect tire tread wear estimation, performing a data fusion of the indirect tire tread wear estimation with the direct tire tread wear measurement when available, estimating a percentage tire life remaining and a mileage to end of tire life, and estimating a refined tire tread wear calibration coefficient for performing future indirect tire tread wear estimations.

Abstract: 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.

Abstract: A method for determining a tire tread wear estimation of a tire includes receiving, by a controller, a direct tire tread wear measurement, when available, performing an indirect tire tread wear estimation, performing a data fusion of the indirect tire tread wear estimation with the direct tire tread wear measurement when available, estimating a percentage tire life remaining and a mileage to end of tire life, and estimating a refined tire tread wear calibration coefficient for performing future indirect tire tread wear estimations.