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This paper presents a nonlinear control approach to achieve good performances in vehicle path following and collision avoidance when the vehicle is driving under cruise highway conditions. Nonlinear model predictive control (NLMPC) is adopted to achieve online trajectory control based on a simplified vehicle model. GMRES/Continuation algorithm is used to solve the online optimization problem. Simulations show that the proposed controller is capable of tracking the desired path as well as avoiding the obstacles.

Aim of this study is to analyze the benefits of the measures provided by smart tyres on tyre-road friction coefficient and vehicle sideslip angle estimation. In particular, a smart tyre constituted by 2 tri-axial accelerometers glued on the tyre inner liner is considered which is able to provide the measures of the tyre-road contact forces once per wheel turn. These measures are added to the ones usually present onboard vehicle (steer angle, lateral acceleration and yaw rate) and following included into an Extended Kalman Filter (EKF) based on a single-track vehicle model. Performance of the proposed observer is evaluated on a series of handling maneuvers and its robustness to road bank angle, tyre and vehicle parameters variation is discussed.

The Linear Time Varying (LTV) Model Predictive Control (MPC) is a linear model predictive control based on linearization of the nonlinear vehicle model. The linearization is carried out consideing each vehicle state. The developed model is able to steer to avoid obstacles and follow a given path. Once the optimal parameters are found, both in terms of trajectory following and real-time performances, the LTV-MPC is used for assessing the limit vehicle conditions as a function of the vehicle forward target speed, the obstacle shape as well as the road conditions (both dry and wet road conditions were taken into account). It is shown that, to avoid collisions, given performances of the vehicle brakes and of the mounted sensors are required.

For passenger cars, individual tyre model parameters, used in vehicle models able to simulate vehicle handling behavior, are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. Indoor experiments on agricultural tyres are instead more challenging and thus generally not performed due to tyre size and applied forces. However, the knowledge of their handling characteristics is becoming more and more important since in the next few years, all agricultural vehicles are expected to run on ordinary asphalt roads at a speed of 80km/h. The present paper presents a methodology to identify agricultural tyres' handling characteristics based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers, J-turns, etc.), instead than during indoor tests.