Performance measurement in railway remote driving implementations - Patrick Urassa; Nils O. E. Olsson; Albert Lau; Pranjal Mandhaniya; Bjørn Andersen (IET Intelligent Transport Systems)
Abstract Remote driving, a well‐matured technology in various industries, is relatively new to the railway sector but appears to be a promising solution for achieving advanced automation, especially for conventional trains. The shift from traditional in‐cab driving to automated train operation, especially remote operations is a complex and ongoing process, with laboratory and field tests being conducted to examine its viability. This transition presents numerous areas that require further investigation and development. This study delves into these unexplored areas, examining various metrics that could be pivotal during the introduction of railway remote driving. The research adopts a mixed‐method approach, employing a triangulation technique in data collection to address the research question on performance indicators for railway remote driving. Through an extensive literature review, benchmarking, and expert surveys, the study pinpoints several performance indicators crucial for assessing the operational effectiveness of remote railway operations. The developed indicators were validated using the two‐round Delphi method, with 9 out of 13 being deemed essential by the panel of experts. The list of these indicators is the key finding in the study. They are: latency, data transfer rate, cybersecurity measures, video quality and camera stability, perception, system integration, permanent connection check, driver vitality check, and organizational aspects. The study contributes to filling the existing research gap and serve as a cockpit or instrumental panel in the implementation of remote operations, thus facilitating the transition towards more automated and remotely operated systems.