Tire tread health is essential for safe operation of a passenger vehicle. Worn out tires significantly increases the risk of traffic accidents and hydroplaning. This thesis investigates the possibility to detect tire tread wear by estimating the effective rolling radius of a tire. The effective rolling radius of a tire is affected by several different factors. As to not confuse change in external factors with actual tire tread wear, there is therefore a need to compensate the effective rolling radius to nominal conditions, to make sure that the change in compensated rolling radius is only due to the tire tread wear. This raises the questions: how can the effective rolling radius be estimated? Can it be compensated with respect to external factors? The behavior of the tire changes between different tire models. This is because different models uses different materials, patterns, internal structure etc. This raises an additional question. Can a compensation model with the same parameter values be used in all vehicles of the same type no matter the tires of the vehicle, or is there a need for an adaptive compensation model that adapts the parameters to the current tire? This thesis investigates how the estimation of the tires effective rolling radius can be improved by estimating the velocity using sensor fusion between GPS- and IMU-signals. This was done using an Extended Kalman Filter. Furthermore, this thesis proposes different ways of compensating a tires effective rolling radius with respect to external factors and compares these methods with each other to obtain the most efficient compensation method. After finding an appropriate compensation method, further investigations regarding the need of adaptivity between tires was performed to find out if the compensation factors can be used on the same vehicle model with different tire sets. Ultimately, the investigations showed that the estimation of the effective rolling radius of a tire using sensor fusion was not fruitful due to limitations set by the IMU. If the vehicle had been equipped with a 6-axis IMU instead of a 3-axis IMU, this method might be feasible. The method that directly calculates the effective rolling radius from GPS-velocity and wheel speed gave a more accurate rolling radius signal. The compensation of the effective rolling radius can be achieved with respect to velocity, tire pressure and tire temperature. The most advantageous compensation method proposed in this thesis was a polynomial compensation model. Lastly, when investigating the need of adaptive compensation factors it was found that these compensation factors needs to be adaptive between tire sets.