An intelligent multiple-articulated rubber-tired vehicle based on automatic steering and trajectory following method

Abstract

For manually driven rubber trams to track, virtual tracks can easily cause driver fatigue. Therefore, based on visual navigation, an automatic steering and trajectory following method are proposed. First, the vehicle kinematic and dynamic model of the Delight Tram is proposed. Then, the automatic steering and trajectory following methods are introduced, which are based on model prediction control and Ackermann steering theory, respectively. Finally, the effectiveness of the proposed methods has been evaluated via both multi-body dynamic simulations and road tests under various working conditions. The results show that the vehicle has excellent steering and trajectory following ability whether in a transient phase or a steady-state circumference. Furthermore, the steering system can stabilize the vehicle in the whole range of design speed, with a smaller computational cost.