Train-Centric Communication Based Autonomous Train Control System
Haifeng Song, Shigen Gao, Yidong Li, Ling Liu, Hairong Dong
Abstract
Driverless train control systems are becoming popular in the world. Notably, this technology has already been applied for several years. However, these kinds of Automatic Train Operation systems are still under the framework that network elements and movement authority are generated from the ground control center. Hence, the aforementioned rail systems are “automated” but not “autonomous,” and the architecture utilization and train tracking interval are limited. With the development of advanced sensors and control algorithms, the train intends to be equipped with a decision-making capability. In order to further improve train movement coordination and efficiency, an Autonomous Train Control System (ATCS) is proposed. This paper provides three main contributions: Firstly, the system structure is described, and the information following in ATCS is discussed with general operation scenarios. Secondly, data isolation is broken under ATCS, and data prediction and edge-based information fusion are applied to process the real dynamic data and estimate the train's speed and position. Thirdly, with the assistant of data fusion, model predictive and data-based control methodologies are discussed.