Longitudinal control of Autonomous-rail Rapid Tram in platooning using Model Predictive Control

Through the formation control, the virtual connection of two tram can be effectively relieved, which can effectively alleviate the passenger demand during peak passenger flow, flexibly decompose when the passenger flow is low, which can effectively deal with tidal passenger flow. This paper presents a method for longitudinal tram platooning control of the Autonomous-rail Rapid Tram (ART) based on cooperative adaptive cruise control(cooperation ACC). The following tram in the CACC formation will sense the position of the leading tram and adjust the speed to avoid collision. In order to realize wireless information transmission between different vehicles through V2V, and transfer information including position, speed, acceleration or road intersection status to assist the tram formation decision and planning. On the other hand, in order to improve control performance, it is important to design a closed-loop controller that takes into account vehicle dynamics. In this article, we try to solve this problem by using the Model Predictive Control (MPC) algorithm, which can explicitly deal with the constraints imposed on the actuator or the acceleration response. Finally, through hardware-in-loop simulation verification, we verified that the developed platooning control has a faster response speed and higher comfort even in traffic jam scenarios.