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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.

Many studies have been carried out to optimize the aerodynamic performances of a single car or a single vehicle. In present days the traffic increases and sophisticated technologies are developing to guarantee the drivers safety, to minimize the fuel consumption and be more environmentally friendly. Within this research area a new technique that is being studied is Platooning: this means that different vehicles travel in a configuration that minimizes the aerodynamic drag and therefore the fuel consumption and the longitudinal space. In the present study platoons with different vehicles and configurations are taken into account, to analyze the influence of car shape and relative distance between the vehicles. The research has been carried out using CFD techniques to investigate the different flow fields around different platoons, while wind tunnel tests have been used to validate the results of the CFD simulations.

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.