Moving-Window Integrated Physics-Data-Based Modeling of Lateral Dynamics

This paper proposes a moving-window Integrated Physics-Data-Based (IPDB) modeling method for the lateral dynamics of autonomous vehicles. The IPDB modeling method initiates from the fundamental physical principles of vehicle motions and express the nonlinear lateral dynamics directly by data snapshots in a moving window. Therefore, the IPDB model is physically interpretable and inherits adaptiveness of data-driven approaches. Specifically, the physics-based lateral dynamics are expressed into affine linear parameter-varying (LPV) formulation and system matrices can be successfully represented by the data snapshots in finite-length moving window without training or calibrations. After that, the CarSim simulations are conducted for data collection and to derive IPDB model. The data-efficient and online adaptive characteristics are validated by the data under several driving scenes. Simulation results confirm that the moving-window IPDB model only uses a small amount of data, but can exhibit great online modeling capability with strong adaptation and excellent model accuracy under varying driving scenarios.