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In this paper, longitudinal automated vehicle control for platooning is investigated by both experiment and simulation. Two-car platooning is realized by controlling the throttle of the following car. A vehicle model which is used for simulation and as a control model for experiment is constructed. The model contains nonlinear elements of the engine, the torque converter and the automatic transmission. Comparison of sliding control(SC) and PID control(PID) is done under various conditions. It is shown that especially under large initial deviation from the target state sliding control has better stability and more rapid convergence than PID control.

Vehicle lateral states such as lateral distance at a preview point and heading angle are indispensable for lane keeping control systems, and such states are normally estimated by fusing signals from an onboard vision system and inertial sensors. However, the sampling rates and measurement delays are different between the two kinds of sensing devices. Most of the conventional methods simply neglect measurement delay and reduce sampling rate of the estimator to adapt to the slow sensors/devices. However, the estimation accuracy is deteriorated, especially considering the delay of visual signals may not be constant. In case of electric vehicles, the actuators for steering and traction are motors that have high control frequency. Therefore, the frequency of vehicle state feedback may not match the control frequency if the estimator is infrequently updated. In this paper, a multi-rate estimation algorithm based on Kalman filter is proposed to provide lateral states with high frequency.

Recently, car-sharing services using ultra-compact mobilities have been attracting attention as a means of transportation for one or two passengers in urban areas. A platooning system consisting of a manned leader vehicle and unmanned follower vehicles can reduce vehicle distributors. We have proposed a platooning system which controls vehicle motion based on the relative position and posture measured by non-contact coupling devices installed between vehicles. The feasibility of the coupling devices was validated through a HILS experiment. There are two basic requirements for realizing our platooning system; (1) all devices must remain coupled and (2) follower vehicles must be able to track the leader vehicle trajectory. Thus, this paper proposes two vehicle control method for satisfying those requirements. They are the “device coupling and trajectory tracking merging method” and the “trajectory shifting method”.