Commonly, Bicycle model is used to vehicle dynamics modeling. This model has some advantages such as low complexity of differential equations, but this model consists of tire dynamics that has unpredictable lateral and longitudinal tire parameters. These parameters should be estimated by online parameters estimation procedures such as unscented or extended Kalman filtering.
The aim of this project is fuzzy modeling of lateral and longitudinal vehicle dynamics. To reach this purpose, first kinematic variables of the vehicle should be measured by designed Inertial Navigation System (INS) and aid sensors, then these variables could be used as inputs and outputs of fuzzy vehicle dynamics model. In lateral vehicle dynamics, steering wheel angle and velocity of the vehicle are inputs and resulted attitude is output. this model can be used in driver assistance systems structure to lose the risk of over or under-steering of the vehicle in corners.
- Fuzzy Modeling of Driver/Vehicle Behavior in Lateral Motions Using PSO/ANFIS algorithm (In progress).