Two frameworks based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented. A given trajectory represents the driver intent. An MPC has to safely avoid obstacles on the road while trying to track the desired trajectory by controlling front steering angle and differential braking. We present two different approaches to this problem. The first approach solves a single nonlinear MPC problem. The second approach uses a hierarchical scheme. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model in order to avoid an obstacle. At the low-level an MPC controller computes the vehicle inputs in order to best follow the high level trajectory based on a nonlinear vehicle model. This article presents the design and comparison of both approaches, the method for implementing them, and successful experimental results on icy roads.

‡Research/Advanced Engineering, Ford Motor CompanyIn this article, the cornering stiffness estimation problem based on the vehicle bicycle (one-track) model is studied. Both time-domain and frequency-domain-based methods are analyzed, aiming to estimate the effective cornering stiffness, defined as the ratio between the lateral force and the slip angle at the two axles. Several methods based on the bicycle model were developed, each having specific pros/cons related to practical implementations. The developed algorithms were evaluated on the basis of the simulation data from the bicycle model and the CarSim TM software. Finally, selected algorithms were evaluated using experimental data.

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We present a nonlinear analysis of vehicle motion using a hybrid physical/dynamic tire/road friction model. The advantage of the proposed LuGre dynamic tire/road friction model is the simple and attractive structural properties for real-time friction estimation and control. Moreover, the model provides a property of capturing coupling effects between the longitudinal and lateral friction forces. We take advantages of these properties and analyze the vehicle lateral motion stability. We have shown that the existence of longitudinal slip affects the lateral motion stability. The quantitative analysis and relationship are also demonstrated through numerical simulation examples.