Assessing network cognition in the Dutch railway system: insights into network situation awareness and workload using social network analysis

Julia C Lo,Sebastiaan A Meijer

doi:10.1007/s10111-019-00546-7

Abstract

This study takes upon a group cognition perspective and investigates the cognition of railway traffic operations, in particular railway traffic and passenger traffic control. A table-top simulation environment is used to conduct the study, in which its design principles are elaborated upon. Network cognition is operationalized through communication content and flow and studied through social network analysis (SNA). SNA centrality metrics, such as degree, closeness and betweenness, are assessed in these networks. As part of the study, two cases are compared where operational procedures for disruption mitigation are varied. The dependent variables are the different types of communication network structures that are conceptualized for communication flow and semantic network structures for communication content. Although the quantitative comparisons between the two operational procedures regarding their communication flow and semantic networks showed no significant differences, this study provides a methodology to compare different conditions.

Highlights

When train traffic and network operations become disrupted, railway traffic control is mostly a job for humans, sometimes with the help of decision-support tools
Four roles—namely passenger train driver (TD passenger), driver for shunting trains at stations (TD shunting), one back office coordinator (BO) and an emergency coordinator (EC)—were performed by two facilitators and included in the analysis
The nodes are ordered in such a way to visualize the informal hierarchical structure in terms of operational levels, that is, operational duties in the field, followed by control room operations at a local (TTC and regional passenger traffic junction coordinator (RPTJC)), regional (RNC and regional passenger traffic monitor (RPTM)) or national level (NNC, national passenger traffic controller (NPTC) and back office)

Summary

Introduction

When train traffic and network operations become disrupted, railway traffic control is mostly a job for humans, sometimes with the help of decision-support tools. Railway traffic controllers are challenged since the interpretation of a situation implies coupling a large number of often fuzzy indications, of which the consequences are combinatorially explosive. To these complex and ill-defined situations, the work that railway traffic controllers carry out is under high time pressure and with high stakes, often in close collaboration. As there is a need to test the impact of alternative modes of the system, the Dutch railway infrastructure organization ProRail turns to single-actor human-in-the-loop and multiactor table-top simulation environments as a platform to test future configurations of the system and to train personnel to work with them. Multi-actor table-top simulation environments are the most commonly used due to their short development time and low development costs and were used in the current study (e.g., Lo et al 2013; Meijer 2012)

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