Radio communication-based method for analysis of train driving in an ERTMS signaling environment

Rosberg, Tomas; Thorslund, Birgitta · 2022 · DOAJ

DOI: 10.1186/s12544-022-00542-5

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Summary

This paper addresses the need for efficient data collection methods to analyze train driving behavior within the European Rail Traffic Management System (ERTMS) environment. As ERTMS replaces traditional lineside signaling with in-cab signaling, understanding how drivers interact with the new system is critical for optimizing capacity and signal planning. Traditional measurement methods, such as GPS or onboard data recorders, are often time-consuming, logistically complex, or subject to legal restrictions. The authors propose a novel, cost-effective method that utilizes standardized radio communication data (ETCS Level 2 protocol) exchanged between the Radio Block Center (RBC) and the train’s On-Board Unit (OBU) to derive train dynamics, specifically focusing on braking characteristics at single-track meeting points. The methodology involves developing software to extract and process ETCS message logs, specifically the Train Position Report (TPR) and Movement Authority messages. To address the low resolution of raw speed data in the protocol, the authors tested three alternatives for calculating speed: using the raw reported speed variable, calculating average speed from reported position and time, and processing reported position with an algorithm that accounts for odometry uncertainty. The validity of these methods was assessed by comparing them against high-precision GPS measurements collected over 19 runs on the Ådalsbanan line in Sweden. Additionally, the study analyzed deceleration patterns for 81 trains braking toward stop signals with different release speeds (15 km/h vs. 40 km/h) or scheduled stops without signal restrictions. The results indicate that the radio-based method is a feasible and valid alternative to traditional GPS measurements. Among the three calculation alternatives, the processed position method (Alternative 3) proved most promising, offering better accuracy by mitigating the low resolution of raw speed data and handling position uncertainty effectively. The validation showed that the method could accurately capture train dynamics, with acceleration errors within acceptable limits for capacity analysis. Regarding braking behavior, the study found that deceleration patterns varied significantly depending on the signal target and release speed. Drivers exhibited different braking profiles when approaching signals with 15 km/h versus 40 km/h release speeds, and when stopping at platforms without restrictive signals, highlighting the impact of signal design on driver behavior and line capacity. The significance of this work lies in providing a scalable, efficient tool for analyzing train dynamics in ERTMS environments without the logistical burdens of physical measurement equipment. By leveraging existing radio communication logs, infrastructure managers and researchers can more easily study the interaction between signaling design and driver behavior. This approach supports the broader ERTMS rollout by offering data-driven insights into how signal planning and release speeds affect operational capacity and drivability, ultimately aiding in the optimization of rail network performance.

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