An artificial potential field approach for virtual coupling train control with complete braking curve supervision

工程类 汽车工程 领域(数学) 联轴节(管道) 控制(管理) 动态制动 控制工程 计算机科学 模拟 制动器 机械工程 人工智能 数学 纯数学
作者
Yuqing Ji,Egidio Quaglietta,Rob M.P. Goverde,Dongxiu Ou
出处
期刊:Transportation Research Part C-emerging Technologies [Elsevier BV]
卷期号:173: 105050-105050 被引量:33
标识
DOI:10.1016/j.trc.2025.105050
摘要

• An artificial potential field approach is proposed for VC train control. • A complete braking curve supervision is used for VC train separation. • A homogeneous strip train model considers realistic train dynamics. • Different combinations of heterogenous trains are considered. • Promising train control performances are obtained in a real case study. In response to the escalating demand for rail transport, the concept of Virtual Coupling (VC) train operations is progressively gaining ground within the railway sector. The concept of VC aims at reducing safe train separation to less than the absolute braking distance by letting trains move synchronously in radio-connected convoys. One of the major concerns associated with VC is ensuring safe train separation considering realistic risk factors, such as heterogeneous train braking performances and varying track conditions. To address such a safe train separation problem under VC, this paper proposes a novel train control model based on the Artificial Potential Field (APF) method to safely supervise the complete braking process of trains moving in a VC convoy. The proposed model uses a homogeneous strip representation of train length and a Dynamic Safety Margin (DSM) to take into account accurate train dynamics as well as potential risk factors, due to different train acceleration/braking rates, communication delays, unexpected emergency train braking applications, and position measurement errors. The method has been applied to the case of a high-speed line in China. Results show that the APF-based control method can effectively adapt to real-time variations in train dynamics and the operational environment to safely supervise the complete train braking process and avoid collisions even in the case of unplanned emergency braking applications. The proposed APF-based approach shows promising real-time performance which can further contribute to advancing the state of the art on safe train control under VC signalling.
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