Internet of Things in the Railway Domain: Edge Sensing System Based on Solid-State LIDAR and Fuzzy Clustering for Virtual Coupling

Abstract

Recent advances in wireless communication, sensing and processing technologies are fostering novel research and innovation opportunities in areas such as Industry 4.0, Smart Cities and Intelligent Transportation Systems. In particular, the railway domain is envisioned to have important breakthroughs in terms of cost-efficiency, self-management, and reliability in the operation of the rolling stocks and infrastructures. Some of these key objectives are been addressed by the concept of Railway Virtual Coupling, which is a promising solution where the capacity of the tracks is highly improved by means of reducing the distance between adjacent trains, and the physical connection between train's compositions, through accurate Vehicle-to-Vehicle communication systems. In this work a new approach towards supporting the information dynamically exchanged by the trains is proposed, with the design and implementation of a Solid-State LIDAR based sensing system to provide an accurate, robust and low-latency on-board distance detection system between trains. The combination of a long-range distance sensor, an Internet of Things (IoT) edge hardware platform and a fuzzy clustering approach for distance detection of the object of interest allows obtaining very accurate results to support the virtual coupling maneuvers. The system implementation has been tested in a real railway scenario, where several coupling and distance detection maneuvers have been performed to verify the operation of the proposed system in an actual application context. This represents one of the first dedicated distance detection tests of this kind under real dynamic conditions documented in the literature towards railway virtual coupling.INDEX TERMS Edge nodes, Internet of Things, LIDAR sensing, railway application, wireless sensor networks.

An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport

“…The classification result is subsequently used for timely maintenance decision making (Figure 12), thus reducing maintenance time and costs and avoiding unscheduled overhauls [185]. Sources of analysis data in railways can be wide and varied, such as (i) intelligent sensor networks on-board freight trains [114], (ii) optical sensors such as LIDAR (light detection and ranging) devices on-board trains, which are used for accident prevention [186], and (iii) cameras and other sensors aboard unmanned aerial vehicles (UAVs) used for infrastructure monitoring [187], just to name a few. tonomous vehicles' traffic for multimodal transport is a relatively recent field of research [182], so experts from other areas such as mechatronics are often required [152] to carry out the analysis with sufficient levels of accuracy (see, e.g., [36]).…”

Virtual Coupling in Railways: A Comprehensive Review

“…Finally, the work [203] proposed an approach for dynamic information exchange between trains. They combine a long-range distance sensor, an IoT edge hardware platform, and a fuzzy clustering approach to support VC maneuvers.…”

Sustainable Transport and Mobility—Oriented Innovative Startups and Business Models

“…The Internet of Trains has been applied to rail transport, specifically to rolling stock connected to other infrastructure elements [47,62,63]. For some time now, it has been enabling various improvements, among which we can mention: smart ticketing, railroad analytics, dynamic route planning, optimal train movement, and capacity planning.…”